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Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-qRv1wrtgsmM.mp4 113.43 MB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.mp4 107.2 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.mp4 105.02 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2-qEteyPNRSwU.mp4 104.62 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/01. Introduction-TdopVWltgqM.mp4 87.9 MB
Part 06-Module 01-Lesson 03_Analyzing Data/19. Geospatial Indexes-iGnSNfzaLf4.mp4 67.91 MB
Part 06-Module 01-Lesson 03_Analyzing Data/11. Unwind Operator-6wBjB3Ca5H4.mp4 58.48 MB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-Zyq0FQ0XO3o.mp4 56.63 MB
Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example-LCZG4wlEFXE.mp4 53.74 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/29. Lessons Learned-_dnp6ItYOdA.mp4 52.87 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/49. The Future of Data Visualizations--CWbVBYBYWU.mp4 52.69 MB
Part 12-Module 01-Lesson 05_Interview Practice/04. Query a SQL database-UVSFLWdAKl4.mp4 51.16 MB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources-OYl-saB2vWE.mp4 50.48 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/15. JSON Playground-la_rboWWjQI.mp4 49.97 MB
Part 12-Module 01-Lesson 03_Interview Fails/04. Interviewing Fails Lyla Fujiwara-CgK2HxdJzc8.mp4 49.74 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.mp4 49.6 MB
Part 14-Module 01-Lesson 05_Analyzing Results/16. Analyzing Multiple Metrics-mbHnQ_EdrZ8.mp4 49.58 MB
Part 04-Module 03-Lesson 01_Investigate a Dataset/05. Investigate A Dataset Project Walkthrough Final-OtDZCYxbHB4.mp4 49.39 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/23. Learning Effects-nFpIDWPUDm8.mp4 49.04 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/09. Using CSV Module--S4vc6tvxoI.mp4 48.81 MB
Part 06-Module 01-Lesson 03_Analyzing Data/17. Indexes-tSgPhxZdhLk.mp4 48.03 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2-siuolDaB4eU.mp4 47.08 MB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.mp4 45.22 MB
Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.mp4 45.15 MB
Part 06-Module 01-Lesson 03_Analyzing Data/03. Example of Aggregation Framework-pOJAW4jTjr0.mp4 44.77 MB
Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes-vL9FcO_9dCA.mp4 44.6 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-gs4qKb-0Lfs.mp4 44.51 MB
Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-cXluuqCVg18.mp4 42.14 MB
Part 05-Module 01-Lesson 05_Data Quality/08. Example Using our Blueprint-G3RjHqqQSgE.mp4 41.9 MB
Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.mp4 40.96 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/12. Metric Definition and Data Capture-qtVm_stSHuM.mp4 40.93 MB
Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators-cleAY1-Jboc.mp4 40.81 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-xOSypbjALh4.mp4 40.78 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.mp4 40.68 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/07. Parsing XML-SIsG0HYYwY4.mp4 40.4 MB
Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.mp4 40.21 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.mp4 39.96 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.mp4 39.96 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/14. Filtering and Segmenting-DETCNMqnnKw.mp4 38.69 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/10. Reviewing our Street Name Audit-pH3VusOq9tc.mp4 38.3 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2-1JRk6dgQhkE.mp4 38.29 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/25. Dot Notation-OcPW6xp8DfE.mp4 37.87 MB
Part 06-Module 01-Lesson 03_Analyzing Data/09. Project Operator-_kupbxrZBds.mp4 37.44 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.mp4 37.11 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-W4Xno_vJvZM.mp4 36.73 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/16. Summary Metrics-ghMD3AfjLZc.mp4 36.24 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2-0DyLzS2ux7g.mp4 35.8 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/11. Target Population-HO1Doq8PiCI.mp4 35.62 MB
Part 06-Module 01-Lesson 03_Analyzing Data/15. Multiple Stages Using a Given Operator-0TV8kTw9-HM.mp4 35.29 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion-im8-LLU5J_Y.mp4 35 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size-9w1Yi5nMNgw.mp4 34.84 MB
Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.mp4 34.67 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names-c0IcUiF_kXs.mp4 34.67 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names-c0IcUiF_kXs.mp4 34.67 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/03. Intro to AB Testing-ASQubLvGuxY.mp4 34.46 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.mp4 34.33 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles-eQpSC0IFhv0.mp4 34.31 MB
Part 14-Module 01-Lesson 05_Analyzing Results/18. Gotchas Changes Over Time-P7Hso-EoWvA.mp4 34.13 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.mp4 33.98 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.mp4 33.98 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/26. Up and Down the Visualization Spectrum-NdVf2bY8OnM.mp4 33.64 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/24. Lessons Learned-GonjL0GbNiw.mp4 33.32 MB
Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.mp4 33.28 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel-L2NEk4jvlcY.mp4 33.26 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags-GYhOEJ8EXkg.mp4 32.67 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.mp4 32.67 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.mp4 32.54 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness-T2QI3p0yDNk.mp4 32.49 MB
Part 11-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4 32.42 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error-GTsnxTCjmcM.mp4 32.21 MB
Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.mp4 32.15 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.mp4 31.66 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/08. Defining Metrics Other Techniques-gEO8il9GU3M.mp4 31.57 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/19. Sensitivity and Robustness Example-_I7m7Y4hBOs.mp4 31.15 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.mp4 31.04 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.mp4 30.92 MB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-05jVh4kUbHU.mp4 30.83 MB
Part 11-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.mp4 30.53 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/12. Intro to JSON-Fi7RjhBLobY.mp4 28.93 MB
Part 13-Module 01-Lesson 07_Narrative Structures/07. How to Lie with Bar Charts-75c7a4R4pZ0.mp4 28.91 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/08. Intro to PyMongo-h6M4x9aXx5g.mp4 28.79 MB
Part 13-Module 01-Lesson 07_Narrative Structures/25. Demystifying D3-y7QK8XMHyDQ.mp4 28.48 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview-pOxyL1lwBIw.mp4 28.37 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals-ca8GQmr7B8g.mp4 28.36 MB
Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.mp4 28.35 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/10. Intro to XLRD-TcWtpvLSoG0.mp4 27.64 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/01. Independent Samples-K25Xtqr2WvI.mp4 27.63 MB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.mp4 27.61 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.mp4 27.51 MB
Part 14-Module 01-Lesson 05_Analyzing Results/15. Multiple Metrics Example 3-XByoblkCgfE.mp4 27.47 MB
Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.mp4 27.46 MB
Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2-5xY3sCBHkOk.mp4 27.32 MB
Part 06-Module 01-Lesson 03_Analyzing Data/04. The Aggregation Pipeline-0sl_mbV-fho.mp4 26.84 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.mp4 26.73 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.mp4 26.6 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/10. Inter- vs. Intra-User Experiments-EGE8ddtWIeo.mp4 26.12 MB
Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example--QwMdwqUq9c.mp4 25.94 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/27. Set Unset-bgOky14w77Q.mp4 25.92 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet-yu4mdXybrts.mp4 25.77 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.mp4 25.75 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.mp4 25.75 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.mp4 25.48 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.mp4 25.48 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.mp4 25.43 MB
Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.mp4 25.39 MB
Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.mp4 25.37 MB
Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.mp4 25.27 MB
Part 11-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.mp4 25.09 MB
Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.mp4 25.04 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3-Lx9dhgMZO1s.mp4 24.95 MB
Part 18-Module 03-Lesson 01_Assessing Data/15. Quality Programatic Assessment 1-l-FhDkQRclA.mp4 24.89 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.mp4 24.71 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.mp4 24.68 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/08. Report Results-xNbzHOnSx5Q.mp4 24.59 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.mp4 24.48 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.mp4 24.48 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.mp4 23.98 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.mp4 23.75 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.mp4 23.6 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.mp4 23.44 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.mp4 23.38 MB
Part 11-Module 01-Lesson 09_Clustering/12. Sklearn-3zHUAXcoZ7c.mp4 23.31 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.mp4 23.05 MB
Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.mp4 23.04 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.mp4 22.94 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/46. World Cup Code and Narrative Recap-lnHEvGeech0.mp4 22.94 MB
Part 17-Module 01-Lesson 16_Logistic Regression/29. Model Diagnostics In Python-1Z4eorbfOOc.mp4 22.79 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.mp4 22.31 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.mp4 22.1 MB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.mp4 22.05 MB
Part 06-Module 01-Lesson 03_Analyzing Data/06. Aggregation Operators 1-mRNyMEoCoY0.mp4 22.03 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.mp4 21.97 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-XTS6m5_3fdU.mp4 21.97 MB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.mp4 21.86 MB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.mp4 21.79 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.mp4 21.62 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.mp4 21.57 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.mp4 21.44 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example--DqU-ARfQr4.mp4 21.43 MB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-60IGcSho56o.mp4 21.36 MB
Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.mp4 21.12 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.mp4 21.12 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema-6a-YgbrEACk.mp4 21.06 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.mp4 21.04 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.mp4 21 MB
Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.mp4 20.99 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.mp4 20.96 MB
Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.mp4 20.96 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.mp4 20.89 MB
Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.mp4 20.88 MB
Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.mp4 20.77 MB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.mp4 20.72 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.mp4 20.71 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.mp4 20.63 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.mp4 20.63 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-4QIEdzv6g6w.mp4 20.59 MB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-6MdZ5NUfen0.mp4 20.58 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/20. How Scales Work-4zqm8dz7Z-k.mp4 20.48 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.mp4 20.42 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/31. Layout and Scales-BQWN9ImjUFE.mp4 20.36 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.mp4 20.35 MB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.mp4 20.32 MB
Part 11-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.mp4 20.28 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.mp4 20.19 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.mp4 20.12 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.mp4 20.12 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.mp4 20.05 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data-6mTsvU0ML94.mp4 20 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.mp4 19.99 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson-nWFJ_eOU27I.mp4 19.94 MB
Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.mp4 19.91 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.mp4 19.91 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers-Z0QcZHrflmc.mp4 19.75 MB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.mp4 19.74 MB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.mp4 19.58 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought-vgJ0ZlxzSiw.mp4 19.53 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.mp4 19.43 MB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-GdsLRKjjKLw.mp4 19.32 MB
Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.mp4 19.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.mp4 19.17 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.mp4 19.11 MB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.mp4 19.11 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example-MXukXfzL59E.mp4 19.1 MB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 Solution-CWJZoi_Es84.mp4 19.01 MB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-nTeQi9MjgiA.mp4 19 MB
Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.mp4 18.95 MB
Part 09-Module 02-Lesson 01_Explore and Summarize Data/06. Explore And Summarize Data Walkthrough Final-_OwKKL6SI38.mp4 18.9 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.mp4 18.89 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/07. What is a Projection-QjVNXfI8YRk.mp4 18.86 MB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.mp4 18.85 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.mp4 18.85 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/03. Digging deeper with Trina-i9xslfFp80g.mp4 18.83 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/05. Tableau Dashboards Stories with Trina-i9xslfFp80g.mp4 18.83 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means-hxk2cgdChUw.mp4 18.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.mp4 18.79 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.mp4 18.79 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.mp4 18.78 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-eAukkpVFl5c.mp4 18.78 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-7GeiZ8IVZfE.mp4 18.76 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-7GeiZ8IVZfE.mp4 18.76 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Load D3 in the JavaScript Console-mGyo6dOf0So.mp4 18.62 MB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-E1ePfjcVH3I.mp4 18.59 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.mp4 18.58 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.mp4 18.48 MB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.mp4 18.46 MB
Part 21-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp4 18.44 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.mp4 18.44 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.mp4 18.43 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.mp4 18.41 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.mp4 18.41 MB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.mp4 18.38 MB
Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.mp4 18.32 MB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.mp4 18.31 MB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp4 18.28 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.mp4 18.22 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.mp4 18.11 MB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.mp4 18.11 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.mp4 18.11 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.mp4 18.03 MB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.mp4 18.01 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.mp4 17.98 MB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.mp4 17.82 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.mp4 17.82 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program-FKcIJkTA3GI.mp4 17.66 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.mp4 17.63 MB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.mp4 17.6 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.mp4 17.59 MB
Part 11-Module 01-Lesson 13_PCA/29. When to Use PCA-hJZHcmJBk1o.mp4 17.53 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/17. Multicollinearity VIFs-wbtrXMusDe8.mp4 17.52 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.mp4 17.41 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.mp4 17.37 MB
Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp4 17.37 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.mp4 17.36 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data-TgkBAtaTqJk.mp4 17.36 MB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.mp4 17.33 MB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.mp4 17.31 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.mp4 17.27 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.mp4 17.26 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.mp4 17.26 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.mp4 17.26 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.mp4 17.23 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.mp4 17.13 MB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.mp4 16.99 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.mp4 16.98 MB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.mp4 16.97 MB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.mp4 16.96 MB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.mp4 16.93 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-6pGDwrJHitw.mp4 16.92 MB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.mp4 16.86 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.mp4 16.81 MB
Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.mp4 16.76 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.mp4 16.76 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.mp4 16.76 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.mp4 16.76 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.mp4 16.72 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.mp4 16.68 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.mp4 16.67 MB
Part 11-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn-aCdg-d_476Y.mp4 16.66 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-nXbucNJpP8I.mp4 16.61 MB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.mp4 16.57 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.mp4 16.57 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.mp4 16.55 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.mp4 16.53 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/11. Efficiency of Merge Sort-HKiK5Y-YSkk.mp4 16.53 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.mp4 16.46 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.mp4 16.33 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.mp4 16.17 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.mp4 16.17 MB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.mp4 16.14 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.mp4 16.13 MB
Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.mp4 16.12 MB
Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.mp4 16.11 MB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.mp4 15.97 MB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.mp4 15.95 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.mp4 15.95 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.mp4 15.94 MB
Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files in Python 1-0VZumC18UvQ.mp4 15.94 MB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.mp4 15.93 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.mp4 15.92 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.mp4 15.9 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-PBcd_dxiFbE.mp4 15.9 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-HGYW-skXvY4.mp4 15.88 MB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.mp4 15.78 MB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.mp4 15.71 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.mp4 15.67 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.mp4 15.65 MB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.mp4 15.5 MB
Part 21-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.mp4 15.48 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.mp4 15.46 MB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.mp4 15.42 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.mp4 15.41 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.mp4 15.33 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.mp4 15.33 MB
Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.mp4 15.32 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.mp4 15.3 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.mp4 15.22 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score-pftNHu4uevA.mp4 15.21 MB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.mp4 15.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.mp4 15.19 MB
Part 18-Module 04-Lesson 01_Cleaning Data/17. Flashforward-rfMu3f9O9hQ.mp4 15.17 MB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.mp4 15.11 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.mp4 15.11 MB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.mp4 15.07 MB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.mp4 15.06 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.mp4 15.06 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.mp4 15.01 MB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.mp4 15 MB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.mp4 14.99 MB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.mp4 14.97 MB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.mp4 14.97 MB
Part 11-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.mp4 14.9 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.mp4 14.88 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-KSZ2XLYk4hk.mp4 14.85 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-KSZ2XLYk4hk.mp4 14.85 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.mp4 14.79 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.mp4 14.79 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.mp4 14.72 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.mp4 14.63 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.mp4 14.62 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/01. Introduction-ICKBWIkfeJ8.mp4 14.59 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort-K916wfSzKxE.mp4 14.59 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4 14.57 MB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.mp4 14.57 MB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.mp4 14.57 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.mp4 14.54 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.mp4 14.51 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.mp4 14.5 MB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.mp4 14.42 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.mp4 14.42 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-_Rx9Z-uURQk.mp4 14.42 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-_Rx9Z-uURQk.mp4 14.42 MB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.mp4 14.4 MB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.mp4 14.4 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.mp4 14.38 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.mp4 14.38 MB
Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.mp4 14.34 MB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.mp4 14.34 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.mp4 14.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.mp4 14.3 MB
Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.mp4 14.28 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.mp4 14.27 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.mp4 14.26 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types-ZqRIS9etBqY.mp4 14.25 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types - Data Visualization and D3.js-ZqRIS9etBqY.mp4 14.25 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.mp4 14.19 MB
Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.mp4 14.13 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.mp4 14.12 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.mp4 14.09 MB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.mp4 14.04 MB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.mp4 14.02 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.mp4 13.99 MB
Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.mp4 13.94 MB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.mp4 13.91 MB
Part 18-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1 -XfKc5PtJ7cc.mp4 13.89 MB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.mp4 13.85 MB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.mp4 13.85 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.mp4 13.84 MB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.mp4 13.84 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.mp4 13.83 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.mp4 13.78 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.mp4 13.77 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.mp4 13.76 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/03. Target Your Application to An Employer-X9JBzbrkcvs.mp4 13.74 MB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.mp4 13.73 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-VFS9mGdkU-M.mp4 13.72 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/23. The Facebook Offering-ORLP-phGXMU.mp4 13.68 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.mp4 13.68 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.mp4 13.65 MB
Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.mp4 13.64 MB
Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.mp4 13.64 MB
Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.mp4 13.62 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.mp4 13.47 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.mp4 13.41 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.mp4 13.4 MB
Part 11-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.mp4 13.39 MB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.mp4 13.38 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.mp4 13.37 MB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.mp4 13.36 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/18. Visual Encodings-14FJU1kP6-M.mp4 13.35 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/07. Visual Encodings - Data Visualization and D3.js-14FJU1kP6-M.mp4 13.35 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.mp4 13.33 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.mp4 13.32 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.mp4 13.31 MB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.mp4 13.29 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.mp4 13.27 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test-IdP9Ps2tHgw.mp4 13.27 MB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.mp4 13.26 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.24 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.24 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.mp4 13.24 MB
Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.mp4 13.22 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.mp4 13.22 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.mp4 13.21 MB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4 13.17 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.mp4 13.17 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.mp4 13.13 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-isBv5D88Nso.mp4 13.06 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-isBv5D88Nso.mp4 13.06 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.mp4 13.04 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/02. Exploring data with Trina-sLzULEjMY1E.mp4 13.02 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.mp4 13.02 MB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 1-nDWAZOU3W3U.mp4 12.99 MB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.mp4 12.97 MB
Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.mp4 12.96 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.mp4 12.95 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.mp4 12.86 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.mp4 12.85 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.mp4 12.85 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.mp4 12.85 MB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.mp4 12.85 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.mp4 12.79 MB
Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.mp4 12.78 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.mp4 12.78 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.mp4 12.75 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.mp4 12.74 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.mp4 12.72 MB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.mp4 12.68 MB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.mp4 12.67 MB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.mp4 12.67 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.mp4 12.65 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.mp4 12.64 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.mp4 12.64 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.mp4 12.64 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.mp4 12.62 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.mp4 12.61 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.mp4 12.55 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.mp4 12.54 MB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.mp4 12.52 MB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.mp4 12.5 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.mp4 12.48 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.mp4 12.48 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-X5GWgtZEsgc.mp4 12.47 MB
Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.mp4 12.41 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.mp4 12.38 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.mp4 12.38 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.mp4 12.36 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.mp4 12.36 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.mp4 12.36 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.mp4 12.3 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.mp4 12.29 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.mp4 12.25 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.mp4 12.24 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.mp4 12.23 MB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.mp4 12.2 MB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.mp4 12.19 MB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.mp4 12.19 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.mp4 12.18 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.mp4 12.18 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.mp4 12.18 MB
Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.mp4 12.17 MB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.mp4 12.15 MB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.mp4 12.12 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.mp4 12.08 MB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.mp4 12.08 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.mp4 12.08 MB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.mp4 12.06 MB
Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.mp4 12.04 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/05. Lets Make a Map-mOZuq2JoN-k.mp4 12.03 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.mp4 12 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.mp4 11.98 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/02. Efficiency of Binary Search-7WbRB7dSyvc.mp4 11.97 MB
Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.mp4 11.97 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.mp4 11.95 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.mp4 11.94 MB
Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.mp4 11.89 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/26. Adding and Formatting China's Red Dot-qgTSR_ggTDg.mp4 11.88 MB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.mp4 11.87 MB
Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.mp4 11.85 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.mp4 11.83 MB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.mp4 11.83 MB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.mp4 11.81 MB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.mp4 11.8 MB
Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.mp4 11.8 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.mp4 11.79 MB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.mp4 11.76 MB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.mp4 11.71 MB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.mp4 11.65 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.mp4 11.63 MB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.mp4 11.61 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.mp4 11.56 MB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.mp4 11.54 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4 11.53 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4 11.53 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.mp4 11.53 MB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.mp4 11.53 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.mp4 11.52 MB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.mp4 11.52 MB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.mp4 11.52 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.mp4 11.52 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-TVN4JfSm144.mp4 11.51 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.mp4 11.48 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.mp4 11.47 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.mp4 11.46 MB
Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.mp4 11.46 MB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.mp4 11.42 MB
Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.mp4 11.41 MB
Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.mp4 11.41 MB
Part 21-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.mp4 11.41 MB
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-7JS9PPQ6cN4.mp4 11.4 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.mp4 11.37 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.mp4 11.34 MB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.mp4 11.32 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.mp4 11.32 MB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.mp4 11.27 MB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.mp4 11.26 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small-9ftDJRsfEUI.mp4 11.26 MB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.mp4 11.26 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.mp4 11.25 MB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.mp4 11.22 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.mp4 11.2 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.mp4 11.18 MB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.mp4 11.16 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.mp4 11.16 MB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.mp4 11.14 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.mp4 11.13 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.mp4 11.11 MB
Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.mp4 11.08 MB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.mp4 11.08 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.mp4 11.07 MB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.mp4 11.04 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.mp4 11.04 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.mp4 11.02 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.mp4 11.01 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.mp4 11.01 MB
Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.mp4 11 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.mp4 10.99 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.mp4 10.99 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.mp4 10.98 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.mp4 10.98 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.mp4 10.98 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.mp4 10.98 MB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.mp4 10.96 MB
Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.mp4 10.94 MB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.mp4 10.92 MB
Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.mp4 10.89 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.mp4 10.85 MB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.mp4 10.82 MB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.mp4 10.82 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/11. D3 Chain Syntax and Changing the Navbar-DQ9_HknCsAI.mp4 10.82 MB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.mp4 10.81 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.mp4 10.8 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.mp4 10.8 MB
Part 17-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.mp4 10.77 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/17. Exploring Student Engagement-6QLiscx_zIY.mp4 10.76 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.mp4 10.76 MB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.mp4 10.76 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.mp4 10.75 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.mp4 10.75 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.mp4 10.75 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.mp4 10.73 MB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.mp4 10.71 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.mp4 10.7 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.mp4 10.68 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.mp4 10.68 MB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.mp4 10.67 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.mp4 10.67 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.mp4 10.67 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.mp4 10.65 MB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.mp4 10.64 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-9na_mOWP7pw.mp4 10.63 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-9na_mOWP7pw.mp4 10.63 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.mp4 10.62 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-HTuI3iFzOdU.mp4 10.62 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.mp4 10.61 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.mp4 10.56 MB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.mp4 10.55 MB
Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.mp4 10.53 MB
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.mp4 10.53 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.mp4 10.51 MB
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.mp4 10.5 MB
Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.mp4 10.49 MB
Part 13-Module 01-Lesson 04_Design Principles/06. Common Chart Types-xD2_AU6atqA.mp4 10.48 MB
Part 15-Module 01-Lesson 02_Design Principles/02. Tipos Comuns de Gráficos-xD2_AU6atqA.mp4 10.48 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.mp4 10.45 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.mp4 10.44 MB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.mp4 10.44 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.mp4 10.44 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.mp4 10.43 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.mp4 10.42 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.mp4 10.37 MB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.mp4 10.34 MB
Part 18-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.mp4 10.34 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.mp4 10.34 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.mp4 10.33 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-OVeEr0CSe8U.mp4 10.33 MB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.mp4 10.32 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.mp4 10.3 MB
Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.mp4 10.29 MB
Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.mp4 10.29 MB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.mp4 10.25 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.mp4 10.23 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.mp4 10.22 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation-aeEhfjPFiCw.mp4 10.21 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.mp4 10.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.mp4 10.16 MB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.mp4 10.16 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.mp4 10.15 MB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.mp4 10.15 MB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.mp4 10.14 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team-cuKecPpZ7PM.mp4 10.12 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-LuI1poHmFOw.mp4 10.1 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.mp4 10.1 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.mp4 10.09 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-0SU3cKsWsPw.mp4 10.08 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.mp4 10.07 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.mp4 10.07 MB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.mp4 10.05 MB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.mp4 10.03 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.mp4 9.99 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.mp4 9.98 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.mp4 9.96 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.mp4 9.96 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.mp4 9.94 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.mp4 9.93 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.mp4 9.92 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.mp4 9.91 MB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.mp4 9.91 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-smBMJlpWdVI.mp4 9.91 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-smBMJlpWdVI.mp4 9.91 MB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.mp4 9.9 MB
Part 18-Module 02-Lesson 01_Gathering Data/03. Finding the Best Movies-aq3qM2EkwrI.mp4 9.89 MB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.mp4 9.88 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.mp4 9.88 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.mp4 9.88 MB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.mp4 9.87 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.mp4 9.87 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.mp4 9.86 MB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.mp4 9.85 MB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.mp4 9.83 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.mp4 9.82 MB
Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.mp4 9.82 MB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.mp4 9.81 MB
Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.mp4 9.81 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.mp4 9.8 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-mb1eR8nb9t4.mp4 9.78 MB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.mp4 9.78 MB
Part 19-Module 01-Lesson 02_Design/08. Data Ink Ratio-gW2FapuYV4A.mp4 9.78 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.mp4 9.77 MB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.mp4 9.76 MB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.mp4 9.74 MB
Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.mp4 9.74 MB
Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.mp4 9.72 MB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.mp4 9.72 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.mp4 9.71 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.mp4 9.7 MB
Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.mp4 9.7 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-c8SD8zn5FTo.mp4 9.68 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-c8SD8zn5FTo.mp4 9.68 MB
Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.mp4 9.68 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.mp4 9.68 MB
Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.mp4 9.67 MB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.mp4 9.67 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.mp4 9.65 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.mp4 9.61 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.mp4 9.61 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-0m5k7Ni1O48.mp4 9.6 MB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.mp4 9.6 MB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.mp4 9.6 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.mp4 9.59 MB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.mp4 9.59 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.mp4 9.58 MB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.mp4 9.56 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.mp4 9.55 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -l1pZZKsESAc.mp4 9.53 MB
Part 13-Module 01-Lesson 05_Dimple.js/09. Inspecting Variables and Data-eA8i6-n-Vc4.mp4 9.53 MB
Part 13-Module 01-Lesson 07_Narrative Structures/02. Approaches to Journalism-AxFSDfKP7Zs.mp4 9.5 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4 9.49 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4 9.49 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.mp4 9.49 MB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.mp4 9.48 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.mp4 9.48 MB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.mp4 9.47 MB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.mp4 9.46 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.mp4 9.46 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.mp4 9.44 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.mp4 9.43 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.mp4 9.43 MB
Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.mp4 9.43 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.mp4 9.42 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.mp4 9.42 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.mp4 9.4 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-j5tA__Dq-sQ.mp4 9.39 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.mp4 9.38 MB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.mp4 9.37 MB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.mp4 9.33 MB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.mp4 9.32 MB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.mp4 9.32 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.mp4 9.3 MB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.mp4 9.25 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.mp4 9.25 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.mp4 9.24 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.mp4 9.24 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.mp4 9.2 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.mp4 9.2 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.mp4 9.2 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.mp4 9.2 MB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.mp4 9.19 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.mp4 9.17 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.mp4 9.17 MB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.mp4 9.17 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.mp4 9.16 MB
Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.mp4 9.12 MB
Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.mp4 9.12 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.mp4 9.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.mp4 9.09 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.mp4 9.09 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.mp4 9.07 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.mp4 9.05 MB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.mp4 9.04 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.mp4 9.04 MB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.mp4 9.03 MB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.mp4 9.02 MB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.mp4 9.01 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.mp4 9.01 MB
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.mp4 9 MB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.mp4 8.99 MB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.mp4 8.96 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.mp4 8.94 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.mp4 8.93 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.mp4 8.92 MB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.mp4 8.92 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.mp4 8.9 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.mp4 8.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.mp4 8.89 MB
Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations-hFlVFyatBF0.mp4 8.87 MB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.mp4 8.87 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.mp4 8.86 MB
Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.mp4 8.85 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.mp4 8.82 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/19. Plotting for DataFrames-CDVgPA0Mv2o.mp4 8.81 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/19. Plotting for DataFrames-CDVgPA0Mv2o.mp4 8.81 MB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.mp4 8.79 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.mp4 8.79 MB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.mp4 8.77 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.mp4 8.76 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.mp4 8.76 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -nZq-Y2lfjpY.mp4 8.76 MB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.mp4 8.72 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (After Cleaning)-OF2486euiRE.mp4 8.7 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.mp4 8.7 MB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.mp4 8.7 MB
Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.mp4 8.68 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.mp4 8.67 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.mp4 8.66 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.mp4 8.66 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.mp4 8.64 MB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.mp4 8.63 MB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.mp4 8.63 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.mp4 8.63 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.mp4 8.62 MB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.mp4 8.6 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.mp4 8.59 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.mp4 8.58 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.mp4 8.56 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.mp4 8.56 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.mp4 8.56 MB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.mp4 8.56 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.mp4 8.54 MB
Part 19-Module 01-Lesson 02_Design/13. Using Color-6bAedqD3ilw.mp4 8.47 MB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.mp4 8.46 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.mp4 8.44 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.mp4 8.44 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/34. Completing the Update Function-lUYD6lldDeU.mp4 8.43 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/08. Document Selectors And Queries-xQbKGc-Ptao.mp4 8.41 MB
Part 13-Module 01-Lesson 04_Design Principles/38. Data Ink Ratio-CJouyPxHb84.mp4 8.38 MB
Part 15-Module 01-Lesson 02_Design Principles/17. Data Ink Ratio-CJouyPxHb84.mp4 8.38 MB
Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.mp4 8.37 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.mp4 8.37 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.mp4 8.33 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.mp4 8.32 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.mp4 8.32 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.mp4 8.31 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.mp4 8.31 MB
Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.mp4 8.3 MB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.mp4 8.3 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.mp4 8.3 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.mp4 8.29 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.mp4 8.29 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.mp4 8.27 MB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.mp4 8.27 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.mp4 8.26 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.mp4 8.24 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.mp4 8.24 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-UG924zKZF7U.mp4 8.24 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-UG924zKZF7U.mp4 8.24 MB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.mp4 8.23 MB
Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.mp4 8.22 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.mp4 8.22 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3-mP1P0ybdZqI.mp4 8.2 MB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.mp4 8.2 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.mp4 8.19 MB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.mp4 8.19 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.mp4 8.18 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.mp4 8.17 MB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.mp4 8.16 MB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.mp4 8.13 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.mp4 8.12 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.mp4 8.12 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.mp4 8.12 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.mp4 8.12 MB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.mp4 8.1 MB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet -K-Owid_mf8o.mp4 8.07 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.mp4 8.03 MB
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 Solution-E5tAoCK6GcQ.mp4 8.03 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.mp4 8.03 MB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.mp4 8.01 MB
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.mp4 8 MB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.mp4 7.99 MB
Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.mp4 7.99 MB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.mp4 7.95 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.mp4 7.94 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.mp4 7.93 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.mp4 7.92 MB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.mp4 7.92 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.mp4 7.92 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.mp4 7.91 MB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.mp4 7.9 MB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.mp4 7.89 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/07. Bubble Sort-h_osLG3GmjE.mp4 7.88 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.mp4 7.87 MB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.mp4 7.86 MB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.mp4 7.86 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.mp4 7.85 MB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.mp4 7.84 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-y27MBpbnP48.mp4 7.83 MB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.mp4 7.83 MB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.mp4 7.83 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.mp4 7.82 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.mp4 7.81 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.mp4 7.81 MB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.mp4 7.81 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/15. Nested Selections-y3kJorrQrJg.mp4 7.8 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.mp4 7.79 MB
Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.mp4 7.77 MB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.mp4 7.76 MB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.mp4 7.75 MB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.mp4 7.74 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.mp4 7.74 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.mp4 7.72 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.mp4 7.72 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.mp4 7.72 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.mp4 7.71 MB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.mp4 7.71 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.mp4 7.71 MB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.mp4 7.7 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.mp4 7.7 MB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.mp4 7.69 MB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.mp4 7.69 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.mp4 7.68 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.mp4 7.68 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.mp4 7.68 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-ytUY1_EfxPk.mp4 7.67 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.mp4 7.67 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.mp4 7.65 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.mp4 7.65 MB
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.mp4 7.65 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.mp4 7.64 MB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.mp4 7.63 MB
Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.mp4 7.62 MB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.mp4 7.62 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.mp4 7.61 MB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.mp4 7.61 MB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.mp4 7.61 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.mp4 7.6 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.mp4 7.6 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.mp4 7.59 MB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.mp4 7.59 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.mp4 7.57 MB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.mp4 7.56 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.mp4 7.56 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.mp4 7.56 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.mp4 7.55 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.mp4 7.54 MB
Part 17-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.mp4 7.54 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.mp4 7.54 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.mp4 7.52 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.mp4 7.52 MB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.mp4 7.52 MB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.mp4 7.52 MB
Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.mp4 7.51 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.mp4 7.5 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-aejs122BTzA.mp4 7.49 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.mp4 7.49 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.mp4 7.48 MB
Part 17-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.mp4 7.48 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.mp4 7.48 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.mp4 7.48 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.mp4 7.48 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.mp4 7.46 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.mp4 7.46 MB
Part 14-Module 01-Lesson 05_Analyzing Results/01. Introduction-AyeKXinJ3W8.mp4 7.45 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.mp4 7.44 MB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.mp4 7.43 MB
Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.mp4 7.42 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.mp4 7.42 MB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.mp4 7.41 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.mp4 7.41 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.mp4 7.38 MB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.mp4 7.38 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.mp4 7.38 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.mp4 7.37 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.mp4 7.37 MB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.mp4 7.36 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.mp4 7.35 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.mp4 7.35 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.mp4 7.34 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.mp4 7.33 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.mp4 7.33 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.mp4 7.32 MB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.mp4 7.32 MB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.mp4 7.31 MB
Part 11-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.mp4 7.3 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.mp4 7.29 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.mp4 7.29 MB
Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.mp4 7.29 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.mp4 7.29 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.mp4 7.27 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.mp4 7.26 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.mp4 7.25 MB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.mp4 7.25 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.mp4 7.25 MB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.mp4 7.22 MB
Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.mp4 7.22 MB
Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.mp4 7.22 MB
Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.mp4 7.22 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.mp4 7.22 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.mp4 7.22 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-oR8H9vdtreE.mp4 7.22 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.mp4 7.21 MB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.mp4 7.2 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.mp4 7.2 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.mp4 7.19 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.mp4 7.19 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.mp4 7.16 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.mp4 7.14 MB
Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.mp4 7.14 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.mp4 7.12 MB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.mp4 7.12 MB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.mp4 7.12 MB
Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.mp4 7.11 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.mp4 7.11 MB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.mp4 7.1 MB
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.mp4 7.1 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.mp4 7.09 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.mp4 7.09 MB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.mp4 7.09 MB
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.mp4 7.08 MB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.mp4 7.06 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.mp4 7.05 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.mp4 7.04 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.mp4 7.03 MB
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.mp4 7.03 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.mp4 7.03 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-0tcbCIrJGlM.mp4 7.03 MB
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.mp4 7.02 MB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.mp4 7 MB
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.mp4 7 MB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.mp4 6.99 MB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.mp4 6.98 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.mp4 6.98 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.mp4 6.98 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.mp4 6.98 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.mp4 6.97 MB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.mp4 6.96 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.mp4 6.95 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.mp4 6.95 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.mp4 6.95 MB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.mp4 6.95 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.mp4 6.93 MB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.mp4 6.92 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution-GNAZ2S3igr4.mp4 6.92 MB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.mp4 6.92 MB
Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.mp4 6.91 MB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.mp4 6.88 MB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.mp4 6.88 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.mp4 6.88 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.mp4 6.88 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.mp4 6.88 MB
Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.mp4 6.85 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.mp4 6.84 MB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.mp4 6.83 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.mp4 6.83 MB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.mp4 6.82 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.mp4 6.82 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.mp4 6.81 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.mp4 6.81 MB
Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.mp4 6.8 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.mp4 6.8 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.mp4 6.8 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.mp4 6.79 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.mp4 6.78 MB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.mp4 6.78 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.mp4 6.77 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.mp4 6.77 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.mp4 6.74 MB
Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.mp4 6.73 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.mp4 6.73 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.mp4 6.73 MB
Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.mp4 6.73 MB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.mp4 6.72 MB
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.mp4 6.72 MB
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.mp4 6.72 MB
Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.mp4 6.72 MB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.mp4 6.71 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.mp4 6.71 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.mp4 6.69 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.mp4 6.69 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-bq_gVndUj1U.mp4 6.68 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.mp4 6.68 MB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.mp4 6.68 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.mp4 6.65 MB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.mp4 6.64 MB
Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.mp4 6.63 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.mp4 6.63 MB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.mp4 6.61 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.mp4 6.6 MB
Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables-lXoiI0gx3MU.mp4 6.6 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.mp4 6.59 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.mp4 6.58 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.mp4 6.58 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.mp4 6.58 MB
Part 05-Module 01-Lesson 05_Data Quality/02. What is Data Cleaning-dzqOwmxK3j4.mp4 6.58 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.mp4 6.58 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.mp4 6.57 MB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.mp4 6.57 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.mp4 6.56 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.mp4 6.56 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.mp4 6.56 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.mp4 6.56 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.mp4 6.56 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.mp4 6.55 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.mp4 6.55 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.mp4 6.55 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.mp4 6.54 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.mp4 6.54 MB
Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.mp4 6.54 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.mp4 6.54 MB
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.mp4 6.53 MB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.mp4 6.52 MB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.mp4 6.52 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.mp4 6.52 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.mp4 6.52 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.mp4 6.52 MB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.mp4 6.51 MB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.mp4 6.5 MB
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.mp4 6.5 MB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-i6nppkOcNoE.mp4 6.49 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.mp4 6.49 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.mp4 6.49 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.mp4 6.49 MB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.mp4 6.49 MB
Part 19-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.mp4 6.48 MB
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.mp4 6.48 MB
Part 12-Module 02-Lesson 02_List-Based Collections/03. Arrays-OnPP5xDmFv0.mp4 6.45 MB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.mp4 6.45 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-22sQCo6ovH0.mp4 6.45 MB
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.mp4 6.44 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.mp4 6.43 MB
Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.mp4 6.43 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.mp4 6.42 MB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.mp4 6.42 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.mp4 6.41 MB
Part 13-Module 01-Lesson 07_Narrative Structures/35. Returns in the Data Binding Process-OwyrjSRb2xo.mp4 6.41 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.mp4 6.4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.mp4 6.37 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/07. Fixing Data Types-7NSYtdVrlRE.mp4 6.35 MB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.mp4 6.35 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.mp4 6.34 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.mp4 6.33 MB
Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.mp4 6.33 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.mp4 6.33 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.mp4 6.32 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.mp4 6.32 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.mp4 6.32 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.mp4 6.31 MB
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.mp4 6.31 MB
Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.mp4 6.31 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.mp4 6.3 MB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.mp4 6.3 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.mp4 6.29 MB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.mp4 6.27 MB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.mp4 6.27 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.mp4 6.26 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.mp4 6.26 MB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.mp4 6.26 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.mp4 6.25 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.mp4 6.24 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.mp4 6.24 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.mp4 6.24 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.mp4 6.24 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.mp4 6.24 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.mp4 6.24 MB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.mp4 6.23 MB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.mp4 6.22 MB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.mp4 6.22 MB
Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.mp4 6.21 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.mp4 6.2 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.mp4 6.2 MB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.mp4 6.2 MB
Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.mp4 6.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.mp4 6.2 MB
Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.mp4 6.18 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.mp4 6.18 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4 6.17 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.mp4 6.17 MB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.mp4 6.14 MB
Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.mp4 6.13 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro-jOhaqX_9oy8.mp4 6.13 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort-kUon6854joI.mp4 6.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.mp4 6.09 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.mp4 6.09 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.mp4 6.09 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro-8y2JZ2gEl1k.mp4 6.09 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.mp4 6.09 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.mp4 6.08 MB
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.mp4 6.06 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 08 Lists And Membership Operators V2-JAbZdZg5_x8.mp4 6.06 MB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.mp4 6.05 MB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.mp4 6.05 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.mp4 6.04 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-6UYEM0XUSGQ.mp4 6.04 MB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.mp4 6.03 MB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.mp4 6.02 MB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.mp4 6.01 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.mp4 6.01 MB
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.mp4 6.01 MB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.mp4 6 MB
Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.mp4 6 MB
Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.mp4 5.99 MB
Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.mp4 5.99 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.mp4 5.99 MB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.mp4 5.98 MB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.mp4 5.97 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.mp4 5.97 MB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.mp4 5.97 MB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.mp4 5.96 MB
Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.mp4 5.95 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.mp4 5.95 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.mp4 5.93 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.mp4 5.92 MB
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.mp4 5.92 MB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.mp4 5.92 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.mp4 5.92 MB
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.mp4 5.92 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.mp4 5.91 MB
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.mp4 5.91 MB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.mp4 5.91 MB
Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.mp4 5.9 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.mp4 5.89 MB
Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.mp4 5.89 MB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.mp4 5.89 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.mp4 5.88 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.mp4 5.88 MB
Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.mp4 5.88 MB
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.mp4 5.86 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.mp4 5.86 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.mp4 5.85 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.mp4 5.85 MB
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.mp4 5.84 MB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.mp4 5.83 MB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.mp4 5.83 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.mp4 5.83 MB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.mp4 5.83 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.mp4 5.82 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.mp4 5.82 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/img/party.gif 5.82 MB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.mp4 5.81 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.mp4 5.8 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.mp4 5.8 MB
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.mp4 5.79 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.mp4 5.79 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.mp4 5.77 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.mp4 5.77 MB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.mp4 5.77 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.mp4 5.77 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.mp4 5.77 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.mp4 5.75 MB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.mp4 5.75 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.mp4 5.75 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-rQivl4aJCOI.mp4 5.74 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-rQivl4aJCOI.mp4 5.74 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.mp4 5.74 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.mp4 5.73 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.mp4 5.73 MB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.mp4 5.72 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.mp4 5.72 MB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.mp4 5.7 MB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.mp4 5.69 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.mp4 5.69 MB
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.mp4 5.68 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.mp4 5.67 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.mp4 5.67 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.mp4 5.67 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.mp4 5.66 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/20. Notation for Random Variables-8NxTW1u4s-Y.mp4 5.66 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.mp4 5.66 MB
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.mp4 5.65 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.mp4 5.64 MB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.mp4 5.64 MB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.mp4 5.63 MB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.mp4 5.63 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.mp4 5.63 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.mp4 5.63 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.mp4 5.62 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.mp4 5.62 MB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.mp4 5.62 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.mp4 5.61 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.mp4 5.61 MB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.mp4 5.61 MB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.mp4 5.6 MB
Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.mp4 5.58 MB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.mp4 5.58 MB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.mp4 5.58 MB
Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.mp4 5.58 MB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.mp4 5.57 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.mp4 5.57 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.mp4 5.57 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.mp4 5.57 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.mp4 5.57 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.mp4 5.56 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.mp4 5.56 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.mp4 5.56 MB
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.mp4 5.55 MB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.mp4 5.52 MB
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.mp4 5.5 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-WmJKPUthUPw.mp4 5.5 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-WmJKPUthUPw.mp4 5.5 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.mp4 5.5 MB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.mp4 5.49 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.mp4 5.49 MB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.mp4 5.49 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.mp4 5.48 MB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.mp4 5.47 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.mp4 5.46 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.mp4 5.46 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.mp4 5.46 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.mp4 5.45 MB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.mp4 5.45 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.mp4 5.44 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.mp4 5.44 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.mp4 5.44 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.mp4 5.43 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.mp4 5.43 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.mp4 5.42 MB
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.mp4 5.42 MB
Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.mp4 5.42 MB
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.mp4 5.41 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.mp4 5.39 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.mp4 5.39 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.mp4 5.38 MB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.mp4 5.38 MB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.mp4 5.37 MB
Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.mp4 5.37 MB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.mp4 5.37 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.mp4 5.37 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.mp4 5.37 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.mp4 5.36 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.mp4 5.36 MB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.mp4 5.36 MB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.mp4 5.36 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.mp4 5.35 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.mp4 5.35 MB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.mp4 5.35 MB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.mp4 5.35 MB
Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.mp4 5.35 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.mp4 5.34 MB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.mp4 5.33 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.mp4 5.32 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.mp4 5.32 MB
Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.mp4 5.32 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.mp4 5.31 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.mp4 5.31 MB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.mp4 5.31 MB
Part 18-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.mp4 5.3 MB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.mp4 5.29 MB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.mp4 5.29 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.mp4 5.28 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.mp4 5.27 MB
Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.mp4 5.27 MB
Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.mp4 5.26 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types-seEFuJ-qvlg.mp4 5.26 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types-seEFuJ-qvlg.mp4 5.26 MB
Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.mp4 5.26 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.mp4 5.25 MB
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.mp4 5.25 MB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.mp4 5.25 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.mp4 5.24 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.mp4 5.24 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.mp4 5.24 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.mp4 5.24 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.mp4 5.23 MB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.mp4 5.23 MB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.mp4 5.22 MB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.mp4 5.21 MB
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.mp4 5.21 MB
Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.mp4 5.21 MB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.mp4 5.2 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.mp4 5.2 MB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.mp4 5.19 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.mp4 5.19 MB
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.mp4 5.18 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.mp4 5.18 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.mp4 5.17 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.mp4 5.17 MB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.mp4 5.17 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-RK6CPtXdK5Q.mp4 5.17 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-RK6CPtXdK5Q.mp4 5.17 MB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.mp4 5.15 MB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.mp4 5.14 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.mp4 5.14 MB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.mp4 5.13 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.mp4 5.13 MB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.mp4 5.13 MB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.mp4 5.12 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.mp4 5.12 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.mp4 5.11 MB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.mp4 5.11 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.mp4 5.11 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.mp4 5.11 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.mp4 5.11 MB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.mp4 5.1 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.mp4 5.08 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.mp4 5.08 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.mp4 5.08 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.mp4 5.08 MB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.mp4 5.08 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.mp4 5.07 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.mp4 5.07 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.mp4 5.07 MB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.mp4 5.07 MB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.mp4 5.07 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.mp4 5.07 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.mp4 5.06 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.mp4 5.05 MB
Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.mp4 5.05 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.mp4 5.05 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.mp4 5.03 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.mp4 5.03 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.mp4 5.03 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.mp4 5.03 MB
Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.mp4 5.03 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.mp4 5.02 MB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.mp4 5.02 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.mp4 5.02 MB
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.mp4 5.02 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.mp4 5.01 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.mp4 5.01 MB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.mp4 5.01 MB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.mp4 5 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular-FQoVv3o8vQg.mp4 5 MB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.mp4 5 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.mp4 4.99 MB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.mp4 4.99 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.mp4 4.99 MB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.mp4 4.98 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.mp4 4.97 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.mp4 4.97 MB
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.mp4 4.96 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.mp4 4.95 MB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.mp4 4.92 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.mp4 4.92 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.mp4 4.92 MB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.mp4 4.92 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.mp4 4.91 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.mp4 4.91 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/23. Making Histograms-0J5lNTGbspg.mp4 4.91 MB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.mp4 4.9 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.mp4 4.9 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.mp4 4.9 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.mp4 4.89 MB
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.mp4 4.89 MB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.mp4 4.89 MB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.mp4 4.89 MB
Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.mp4 4.89 MB
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.mp4 4.89 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.mp4 4.89 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.mp4 4.89 MB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.mp4 4.88 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.mp4 4.88 MB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.mp4 4.88 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.mp4 4.87 MB
Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.mp4 4.86 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.mp4 4.86 MB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.mp4 4.85 MB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.mp4 4.84 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.mp4 4.83 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.mp4 4.83 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.mp4 4.82 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.mp4 4.82 MB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.mp4 4.82 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.mp4 4.81 MB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.mp4 4.81 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.mp4 4.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.mp4 4.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.mp4 4.8 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.mp4 4.8 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.mp4 4.8 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.mp4 4.8 MB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.mp4 4.8 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.mp4 4.8 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.mp4 4.8 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.mp4 4.79 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.mp4 4.78 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.mp4 4.78 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.mp4 4.78 MB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.mp4 4.77 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.mp4 4.76 MB
Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.mp4 4.74 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.mp4 4.74 MB
Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.mp4 4.74 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.mp4 4.74 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.mp4 4.74 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.mp4 4.74 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.mp4 4.74 MB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.mp4 4.73 MB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.mp4 4.73 MB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.mp4 4.73 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.mp4 4.71 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.mp4 4.71 MB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.mp4 4.71 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.mp4 4.71 MB
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.mp4 4.71 MB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.mp4 4.71 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.mp4 4.71 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.mp4 4.7 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.mp4 4.69 MB
Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.mp4 4.68 MB
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.mp4 4.68 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.mp4 4.67 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.mp4 4.67 MB
Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.mp4 4.67 MB
Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.mp4 4.67 MB
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.mp4 4.67 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.mp4 4.66 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.mp4 4.66 MB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.mp4 4.66 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.mp4 4.66 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.mp4 4.66 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.mp4 4.66 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.mp4 4.66 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.mp4 4.64 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.mp4 4.64 MB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.mp4 4.64 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.mp4 4.64 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.mp4 4.64 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.mp4 4.64 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.mp4 4.64 MB
Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.mp4 4.63 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.mp4 4.63 MB
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.mp4 4.63 MB
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.mp4 4.63 MB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.mp4 4.62 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.mp4 4.62 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.mp4 4.62 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.mp4 4.62 MB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.mp4 4.62 MB
Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.mp4 4.62 MB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.mp4 4.61 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.mp4 4.61 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.mp4 4.61 MB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.mp4 4.61 MB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.mp4 4.61 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.mp4 4.6 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.mp4 4.6 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.mp4 4.6 MB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.mp4 4.59 MB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.mp4 4.59 MB
Part 13-Module 01-Lesson 07_Narrative Structures/38. Communicating Your Message-wZt6fXEUqQM.mp4 4.59 MB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.mp4 4.59 MB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.mp4 4.59 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.mp4 4.58 MB
Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.mp4 4.58 MB
Part 13-Module 01-Lesson 04_Design Principles/20. Negative Space-3toURbAUt9s.mp4 4.57 MB
Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.mp4 4.57 MB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.mp4 4.57 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.mp4 4.56 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.mp4 4.56 MB
Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.mp4 4.56 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.mp4 4.55 MB
Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.mp4 4.55 MB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.mp4 4.55 MB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.mp4 4.55 MB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.mp4 4.55 MB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.mp4 4.54 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.mp4 4.53 MB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.mp4 4.52 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.mp4 4.51 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.mp4 4.51 MB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.mp4 4.51 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.mp4 4.51 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.mp4 4.51 MB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.mp4 4.5 MB
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.mp4 4.5 MB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.mp4 4.5 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.mp4 4.49 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.mp4 4.49 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.mp4 4.49 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.mp4 4.49 MB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.mp4 4.48 MB
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.mp4 4.48 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.mp4 4.48 MB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.mp4 4.47 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.mp4 4.47 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-28iU6GrDVfU.mp4 4.47 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.mp4 4.47 MB
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.mp4 4.47 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.mp4 4.46 MB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.mp4 4.46 MB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.mp4 4.46 MB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.mp4 4.45 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.mp4 4.45 MB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.mp4 4.44 MB
Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.mp4 4.44 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.mp4 4.43 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-cRb2ONJAvog.mp4 4.43 MB
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.mp4 4.43 MB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.mp4 4.42 MB
Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.mp4 4.4 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.mp4 4.4 MB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.mp4 4.4 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.mp4 4.4 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.mp4 4.4 MB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.mp4 4.37 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.mp4 4.36 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.mp4 4.36 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.mp4 4.36 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.mp4 4.36 MB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.mp4 4.36 MB
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.mp4 4.36 MB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.mp4 4.35 MB
Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.mp4 4.34 MB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.mp4 4.34 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.mp4 4.34 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.mp4 4.33 MB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.mp4 4.33 MB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.mp4 4.32 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.mp4 4.3 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.mp4 4.29 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.mp4 4.29 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.mp4 4.29 MB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.mp4 4.28 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.mp4 4.28 MB
Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.mp4 4.27 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.mp4 4.27 MB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.mp4 4.27 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.mp4 4.26 MB
Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.mp4 4.26 MB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.mp4 4.26 MB
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.mp4 4.26 MB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.mp4 4.25 MB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.mp4 4.25 MB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.mp4 4.25 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.mp4 4.25 MB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.mp4 4.24 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.mp4 4.24 MB
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.mp4 4.24 MB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.mp4 4.24 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.mp4 4.24 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.mp4 4.24 MB
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.mp4 4.23 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.mp4 4.23 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.mp4 4.23 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.mp4 4.23 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.mp4 4.23 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.mp4 4.22 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.mp4 4.22 MB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.mp4 4.22 MB
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.mp4 4.22 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.mp4 4.22 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.mp4 4.22 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.mp4 4.21 MB
Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.mp4 4.21 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.mp4 4.21 MB
Part 17-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.mp4 4.21 MB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.mp4 4.2 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.mp4 4.2 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.mp4 4.19 MB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.mp4 4.19 MB
Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.mp4 4.19 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.mp4 4.19 MB
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.mp4 4.19 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.mp4 4.18 MB
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.mp4 4.18 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.mp4 4.18 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.mp4 4.18 MB
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.mp4 4.17 MB
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.mp4 4.17 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.mp4 4.16 MB
Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.mp4 4.16 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.mp4 4.16 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.mp4 4.16 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.mp4 4.16 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.mp4 4.15 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.mp4 4.15 MB
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.mp4 4.15 MB
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.mp4 4.14 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.mp4 4.14 MB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.mp4 4.14 MB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.mp4 4.13 MB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.mp4 4.11 MB
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.mp4 4.11 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.mp4 4.11 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.mp4 4.11 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.mp4 4.1 MB
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.mp4 4.1 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.mp4 4.09 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.mp4 4.09 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.mp4 4.09 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.mp4 4.09 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.mp4 4.09 MB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.mp4 4.08 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.mp4 4.07 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.mp4 4.06 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.mp4 4.06 MB
Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.mp4 4.06 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-K2sUmPodhqg.mp4 4.05 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-K2sUmPodhqg.mp4 4.05 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.mp4 4.05 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.mp4 4.05 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.mp4 4.04 MB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.mp4 4.04 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.mp4 4.04 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.mp4 4.03 MB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.mp4 4.03 MB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.mp4 4.03 MB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.mp4 4.03 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.mp4 4.02 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.mp4 4.02 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.mp4 4.02 MB
Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.mp4 4.02 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.mp4 4.01 MB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.mp4 4.01 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.mp4 4.01 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.mp4 4.01 MB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.mp4 4.01 MB
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.mp4 4 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.mp4 4 MB
Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.mp4 3.99 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.mp4 3.98 MB
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.mp4 3.98 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.mp4 3.98 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.mp4 3.97 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.mp4 3.97 MB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.mp4 3.96 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.mp4 3.96 MB
Part 13-Module 01-Lesson 04_Design Principles/28. How Visualizations can Save Lives-VUllIatQ3tI.mp4 3.95 MB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.mp4 3.95 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.mp4 3.95 MB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.mp4 3.95 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.mp4 3.95 MB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.mp4 3.95 MB
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.mp4 3.95 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.mp4 3.95 MB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.mp4 3.94 MB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.mp4 3.94 MB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4 3.94 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.mp4 3.94 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/12. Types Of Errors - Part III-Z-srkCPsdaM.mp4 3.94 MB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.mp4 3.93 MB
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.mp4 3.93 MB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.mp4 3.93 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.mp4 3.92 MB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.mp4 3.91 MB
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.mp4 3.91 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.mp4 3.9 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.mp4 3.9 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.mp4 3.9 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.mp4 3.9 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.mp4 3.89 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.mp4 3.89 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.mp4 3.89 MB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.mp4 3.89 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.mp4 3.89 MB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.mp4 3.87 MB
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.mp4 3.87 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.mp4 3.87 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.mp4 3.86 MB
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.mp4 3.86 MB
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.mp4 3.85 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.mp4 3.85 MB
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.mp4 3.85 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.mp4 3.85 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.mp4 3.85 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.mp4 3.84 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.mp4 3.84 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.mp4 3.84 MB
Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.mp4 3.83 MB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.mp4 3.83 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.mp4 3.83 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.mp4 3.83 MB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.mp4 3.83 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.mp4 3.82 MB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.mp4 3.82 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.mp4 3.82 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.mp4 3.81 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.mp4 3.81 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.mp4 3.81 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.mp4 3.8 MB
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.mp4 3.8 MB
Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.mp4 3.79 MB
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.mp4 3.79 MB
Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.mp4 3.79 MB
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.mp4 3.79 MB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.mp4 3.78 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.mp4 3.78 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.mp4 3.78 MB
Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.mp4 3.78 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.mp4 3.78 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.mp4 3.78 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.mp4 3.78 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.mp4 3.77 MB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.mp4 3.77 MB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.mp4 3.76 MB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.mp4 3.76 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.mp4 3.76 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.mp4 3.76 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.mp4 3.75 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.mp4 3.75 MB
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.mp4 3.75 MB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.mp4 3.75 MB
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.mp4 3.75 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.mp4 3.75 MB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.mp4 3.74 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.mp4 3.74 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.mp4 3.74 MB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.mp4 3.74 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.mp4 3.74 MB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_afLozDIcLw.mp4 3.72 MB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.mp4 3.72 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.mp4 3.72 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.mp4 3.72 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.mp4 3.72 MB
Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.mp4 3.72 MB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.mp4 3.72 MB
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.mp4 3.72 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.mp4 3.71 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.mp4 3.71 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.mp4 3.7 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.mp4 3.7 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.mp4 3.69 MB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.mp4 3.69 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.mp4 3.69 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.mp4 3.69 MB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.mp4 3.68 MB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.mp4 3.68 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.mp4 3.68 MB
Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.mp4 3.67 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.mp4 3.67 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.mp4 3.67 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.mp4 3.67 MB
Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.mp4 3.66 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.mp4 3.66 MB
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.mp4 3.66 MB
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.mp4 3.66 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.mp4 3.66 MB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.mp4 3.66 MB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.mp4 3.66 MB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.mp4 3.65 MB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.mp4 3.65 MB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.mp4 3.65 MB
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.mp4 3.65 MB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.mp4 3.65 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.mp4 3.64 MB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.mp4 3.64 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.mp4 3.64 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Calculating the p-value-_W3Jg7jQ8jI.mp4 3.64 MB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.mp4 3.64 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.mp4 3.64 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.mp4 3.63 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.mp4 3.63 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.mp4 3.63 MB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.mp4 3.63 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.mp4 3.62 MB
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.mp4 3.62 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.mp4 3.61 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.mp4 3.61 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.mp4 3.6 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.mp4 3.6 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.mp4 3.6 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.mp4 3.6 MB
Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.mp4 3.59 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.mp4 3.59 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.mp4 3.59 MB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.mp4 3.59 MB
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.mp4 3.59 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.mp4 3.58 MB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.mp4 3.58 MB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.mp4 3.57 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.mp4 3.57 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.mp4 3.57 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.mp4 3.56 MB
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.mp4 3.55 MB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.mp4 3.55 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.mp4 3.55 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.mp4 3.55 MB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.mp4 3.54 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.mp4 3.54 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.mp4 3.54 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.mp4 3.54 MB
Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.mp4 3.53 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.mp4 3.52 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.mp4 3.52 MB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.mp4 3.51 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.mp4 3.51 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.mp4 3.51 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.mp4 3.5 MB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.mp4 3.5 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.mp4 3.5 MB
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.mp4 3.5 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.mp4 3.49 MB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.mp4 3.49 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.mp4 3.48 MB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.mp4 3.48 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.mp4 3.48 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.mp4 3.48 MB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.mp4 3.48 MB
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.mp4 3.48 MB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.mp4 3.47 MB
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.mp4 3.47 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.mp4 3.47 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.mp4 3.47 MB
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.mp4 3.46 MB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.mp4 3.45 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.mp4 3.45 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.mp4 3.45 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.mp4 3.45 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.mp4 3.45 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.mp4 3.45 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.mp4 3.45 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.mp4 3.44 MB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.mp4 3.44 MB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.mp4 3.44 MB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.mp4 3.42 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.mp4 3.41 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.mp4 3.41 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.mp4 3.41 MB
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.mp4 3.41 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.mp4 3.41 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.mp4 3.4 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.mp4 3.4 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.mp4 3.4 MB
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.mp4 3.39 MB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.mp4 3.39 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. 05 Hierarchies-vkHeQcI08yc.mp4 3.38 MB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.mp4 3.38 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-YNuoRW6EyEo.mp4 3.38 MB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.mp4 3.37 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.mp4 3.37 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.mp4 3.37 MB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.mp4 3.37 MB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.mp4 3.37 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.mp4 3.37 MB
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.mp4 3.37 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.mp4 3.36 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.mp4 3.36 MB
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.mp4 3.36 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.mp4 3.36 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.mp4 3.36 MB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.mp4 3.36 MB
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.mp4 3.35 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.mp4 3.35 MB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.mp4 3.35 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.mp4 3.35 MB
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.mp4 3.35 MB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.mp4 3.35 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.mp4 3.35 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.mp4 3.34 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.mp4 3.34 MB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.mp4 3.34 MB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.mp4 3.33 MB
Part 16-Module 03-Lesson 01_Basic SQL/12. Intro To SQL Workspaces-w6XcuK22YCk.mp4 3.32 MB
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.mp4 3.32 MB
Part 17-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.mp4 3.32 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.mp4 3.32 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.mp4 3.32 MB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.mp4 3.32 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.mp4 3.31 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.mp4 3.3 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.mp4 3.3 MB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.mp4 3.3 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.mp4 3.3 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. 03 Tableau Interface-q3E4CCYeIyM.mp4 3.29 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.mp4 3.29 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.mp4 3.29 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.mp4 3.29 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.mp4 3.29 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.mp4 3.29 MB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.mp4 3.29 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.mp4 3.29 MB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.mp4 3.28 MB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.mp4 3.28 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.mp4 3.27 MB
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.mp4 3.27 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.mp4 3.27 MB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.mp4 3.27 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.mp4 3.26 MB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.mp4 3.26 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.mp4 3.26 MB
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.mp4 3.26 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.mp4 3.26 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.mp4 3.25 MB
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.mp4 3.25 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.mp4 3.25 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.mp4 3.24 MB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.mp4 3.24 MB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.mp4 3.24 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.mp4 3.24 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.mp4 3.24 MB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.mp4 3.23 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.mp4 3.23 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.mp4 3.23 MB
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.mp4 3.23 MB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.mp4 3.22 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.mp4 3.22 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.mp4 3.22 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.mp4 3.22 MB
Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.mp4 3.21 MB
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.mp4 3.21 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.mp4 3.2 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.mp4 3.2 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.mp4 3.19 MB
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.mp4 3.19 MB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.mp4 3.18 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.mp4 3.18 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.mp4 3.18 MB
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.mp4 3.18 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.mp4 3.18 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.mp4 3.18 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.mp4 3.17 MB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.mp4 3.17 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.mp4 3.17 MB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.mp4 3.17 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.mp4 3.16 MB
Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.mp4 3.15 MB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.mp4 3.15 MB
Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.mp4 3.15 MB
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.mp4 3.15 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.mp4 3.14 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.mp4 3.14 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.mp4 3.14 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.mp4 3.13 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.mp4 3.13 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.mp4 3.13 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.mp4 3.13 MB
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.mp4 3.13 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.mp4 3.12 MB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.mp4 3.12 MB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.mp4 3.12 MB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.mp4 3.12 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.mp4 3.12 MB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.mp4 3.12 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.mp4 3.11 MB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.mp4 3.11 MB
Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.mp4 3.11 MB
Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.mp4 3.11 MB
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.mp4 3.1 MB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.mp4 3.1 MB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.mp4 3.09 MB
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.mp4 3.09 MB
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.mp4 3.08 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.mp4 3.08 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.mp4 3.08 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.mp4 3.08 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.mp4 3.07 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.mp4 3.07 MB
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.mp4 3.07 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.mp4 3.06 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.mp4 3.06 MB
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.mp4 3.06 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.mp4 3.06 MB
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.mp4 3.06 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes-ODDruv2Qkdg.mp4 3.06 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.mp4 3.06 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.mp4 3.06 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.mp4 3.05 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.mp4 3.05 MB
Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.mp4 3.04 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.mp4 3.04 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.mp4 3.04 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.mp4 3.03 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.mp4 3.03 MB
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.mp4 3.03 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.mp4 3.01 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.mp4 3.01 MB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.mp4 3 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.mp4 3 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.mp4 3 MB
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.mp4 3 MB
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.mp4 3 MB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.mp4 2.99 MB
Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.mp4 2.99 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.mp4 2.98 MB
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.mp4 2.98 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.mp4 2.97 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.mp4 2.97 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.mp4 2.97 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.mp4 2.97 MB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.mp4 2.96 MB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.mp4 2.96 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.mp4 2.95 MB
Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.mp4 2.95 MB
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.mp4 2.95 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.mp4 2.95 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.mp4 2.94 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.mp4 2.94 MB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.mp4 2.94 MB
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.mp4 2.94 MB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.mp4 2.94 MB
Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.mp4 2.94 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.mp4 2.93 MB
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.mp4 2.92 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.mp4 2.91 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.mp4 2.91 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.mp4 2.91 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.mp4 2.91 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.mp4 2.91 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.mp4 2.91 MB
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.mp4 2.91 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.mp4 2.91 MB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.mp4 2.9 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.mp4 2.9 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.mp4 2.9 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.mp4 2.9 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.mp4 2.89 MB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.mp4 2.89 MB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.mp4 2.89 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.mp4 2.89 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.mp4 2.88 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.mp4 2.88 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.mp4 2.88 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.mp4 2.88 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.mp4 2.88 MB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.mp4 2.88 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.mp4 2.87 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.mp4 2.87 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.mp4 2.86 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.mp4 2.86 MB
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.mp4 2.86 MB
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.mp4 2.85 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.mp4 2.85 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.mp4 2.85 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.mp4 2.85 MB
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.mp4 2.85 MB
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.mp4 2.84 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.mp4 2.84 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.mp4 2.84 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.mp4 2.83 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.mp4 2.83 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.mp4 2.83 MB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.mp4 2.83 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.mp4 2.83 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.mp4 2.82 MB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.mp4 2.82 MB
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.mp4 2.82 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.mp4 2.81 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.mp4 2.81 MB
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.mp4 2.81 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.mp4 2.81 MB
Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.mp4 2.81 MB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.mp4 2.81 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.mp4 2.81 MB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.mp4 2.8 MB
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.mp4 2.8 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.mp4 2.8 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.mp4 2.8 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.mp4 2.8 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.mp4 2.8 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.mp4 2.8 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.mp4 2.79 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/09. 06 Practice With Marks And Filters-RPAv7WLkutk.mp4 2.79 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.mp4 2.79 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.mp4 2.79 MB
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.mp4 2.79 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.mp4 2.79 MB
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.mp4 2.79 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.mp4 2.78 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.mp4 2.78 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.mp4 2.78 MB
Part 12-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.mp4 2.78 MB
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.mp4 2.78 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.mp4 2.78 MB
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.mp4 2.77 MB
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.mp4 2.77 MB
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.mp4 2.77 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.mp4 2.77 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.mp4 2.76 MB
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.mp4 2.76 MB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.mp4 2.76 MB
Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.mp4 2.76 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.mp4 2.76 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.mp4 2.76 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.mp4 2.75 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.mp4 2.75 MB
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.mp4 2.75 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.mp4 2.75 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.mp4 2.75 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.mp4 2.75 MB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.mp4 2.74 MB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.mp4 2.74 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.mp4 2.74 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.mp4 2.73 MB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.mp4 2.73 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.mp4 2.72 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.mp4 2.71 MB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.mp4 2.71 MB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.mp4 2.71 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.mp4 2.7 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.mp4 2.7 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.mp4 2.7 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.mp4 2.7 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.mp4 2.7 MB
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.mp4 2.69 MB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.mp4 2.69 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.mp4 2.69 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.mp4 2.69 MB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.mp4 2.69 MB
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.mp4 2.68 MB
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.mp4 2.68 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.mp4 2.68 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.mp4 2.68 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.mp4 2.68 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.mp4 2.68 MB
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.mp4 2.68 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.mp4 2.68 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.mp4 2.68 MB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.mp4 2.67 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.mp4 2.67 MB
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.mp4 2.67 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.mp4 2.67 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.mp4 2.67 MB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.mp4 2.67 MB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.mp4 2.66 MB
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.mp4 2.66 MB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.mp4 2.66 MB
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.mp4 2.65 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.mp4 2.65 MB
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.mp4 2.64 MB
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.mp4 2.64 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.mp4 2.64 MB
Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.mp4 2.64 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.mp4 2.64 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.mp4 2.63 MB
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.mp4 2.63 MB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.mp4 2.63 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.mp4 2.63 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.mp4 2.62 MB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.mp4 2.62 MB
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.mp4 2.62 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.mp4 2.61 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.mp4 2.61 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.mp4 2.61 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.mp4 2.61 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.mp4 2.61 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/03. 01 Connecting To Data-zuJPPSlbW2c.mp4 2.6 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/06. 04 Aggregation Granularity-GuOytlkqdrQ.mp4 2.6 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.mp4 2.59 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.mp4 2.59 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.mp4 2.59 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.mp4 2.59 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.mp4 2.59 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.mp4 2.58 MB
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.mp4 2.58 MB
Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.mp4 2.58 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.mp4 2.58 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.mp4 2.58 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.mp4 2.58 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.mp4 2.58 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.mp4 2.57 MB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.mp4 2.57 MB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.mp4 2.56 MB
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.mp4 2.56 MB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.mp4 2.55 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.mp4 2.55 MB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.mp4 2.55 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.mp4 2.55 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.mp4 2.55 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.mp4 2.55 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.mp4 2.55 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.mp4 2.54 MB
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.mp4 2.54 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.mp4 2.54 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.mp4 2.54 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.mp4 2.54 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.mp4 2.54 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.mp4 2.54 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.mp4 2.54 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.mp4 2.52 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.mp4 2.52 MB
Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.mp4 2.52 MB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.mp4 2.52 MB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.mp4 2.52 MB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.mp4 2.51 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.mp4 2.51 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.mp4 2.51 MB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.mp4 2.51 MB
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.mp4 2.5 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.mp4 2.5 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.mp4 2.5 MB
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.mp4 2.5 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.mp4 2.5 MB
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.mp4 2.49 MB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.mp4 2.49 MB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.mp4 2.49 MB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.mp4 2.48 MB
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.mp4 2.48 MB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.mp4 2.48 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.mp4 2.48 MB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.mp4 2.47 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.mp4 2.47 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.mp4 2.47 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.mp4 2.47 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.mp4 2.47 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.mp4 2.47 MB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.mp4 2.46 MB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.mp4 2.46 MB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.mp4 2.46 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.mp4 2.46 MB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.mp4 2.46 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.mp4 2.45 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.mp4 2.45 MB
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.mp4 2.45 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.mp4 2.44 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.mp4 2.44 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.mp4 2.43 MB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.mp4 2.43 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.mp4 2.42 MB
Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.mp4 2.42 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.mp4 2.42 MB
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.mp4 2.41 MB
Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.mp4 2.41 MB
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.mp4 2.41 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.mp4 2.4 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.mp4 2.4 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.mp4 2.4 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.mp4 2.4 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.mp4 2.39 MB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.mp4 2.39 MB
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.mp4 2.39 MB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.mp4 2.39 MB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.mp4 2.38 MB
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.mp4 2.38 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.mp4 2.38 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.mp4 2.38 MB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.mp4 2.38 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.mp4 2.37 MB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.mp4 2.37 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.mp4 2.37 MB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.mp4 2.37 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.mp4 2.36 MB
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.mp4 2.36 MB
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.mp4 2.36 MB
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.mp4 2.36 MB
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.mp4 2.35 MB
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.mp4 2.35 MB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-e8zSXnyskro.mp4 2.35 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.mp4 2.34 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.mp4 2.34 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.mp4 2.34 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.mp4 2.34 MB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.mp4 2.34 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.mp4 2.33 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.mp4 2.33 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.mp4 2.32 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.mp4 2.32 MB
Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.mp4 2.32 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.mp4 2.32 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.mp4 2.32 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.mp4 2.32 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.mp4 2.32 MB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.mp4 2.32 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.mp4 2.31 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.mp4 2.31 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.mp4 2.31 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.mp4 2.31 MB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.mp4 2.31 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.mp4 2.29 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.mp4 2.29 MB
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.mp4 2.29 MB
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.mp4 2.29 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.mp4 2.29 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.mp4 2.29 MB
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.mp4 2.29 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.mp4 2.28 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.mp4 2.28 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.mp4 2.28 MB
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.mp4 2.28 MB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.mp4 2.28 MB
Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.mp4 2.27 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.mp4 2.27 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.mp4 2.27 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.mp4 2.27 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.mp4 2.27 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.mp4 2.26 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.mp4 2.26 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.mp4 2.26 MB
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.mp4 2.26 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.mp4 2.26 MB
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.mp4 2.25 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.mp4 2.25 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.mp4 2.25 MB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.mp4 2.25 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.mp4 2.25 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.mp4 2.24 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.mp4 2.24 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.mp4 2.24 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.mp4 2.24 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.mp4 2.24 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.mp4 2.23 MB
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.mp4 2.23 MB
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.mp4 2.22 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.mp4 2.22 MB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.mp4 2.22 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.mp4 2.21 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.mp4 2.21 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.mp4 2.21 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.mp4 2.21 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.mp4 2.21 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.mp4 2.21 MB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.mp4 2.21 MB
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.mp4 2.2 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.mp4 2.2 MB
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.mp4 2.2 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.mp4 2.19 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.mp4 2.19 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.mp4 2.19 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.mp4 2.19 MB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.mp4 2.19 MB
Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.mp4 2.19 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API-06LsRU4pmkA.mp4 2.19 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.mp4 2.18 MB
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.mp4 2.17 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.mp4 2.17 MB
Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.mp4 2.17 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.mp4 2.17 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.mp4 2.17 MB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.mp4 2.17 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.mp4 2.17 MB
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.mp4 2.17 MB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.mp4 2.16 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.mp4 2.16 MB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.mp4 2.16 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.mp4 2.16 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.mp4 2.16 MB
Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.mp4 2.16 MB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.mp4 2.15 MB
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.mp4 2.15 MB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.mp4 2.14 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.mp4 2.14 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.mp4 2.14 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.mp4 2.14 MB
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.mp4 2.14 MB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.mp4 2.14 MB
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.mp4 2.13 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.mp4 2.13 MB
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.mp4 2.13 MB
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.mp4 2.13 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.mp4 2.13 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.mp4 2.13 MB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.mp4 2.12 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.mp4 2.12 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.mp4 2.12 MB
Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.mp4 2.12 MB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.mp4 2.12 MB
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.mp4 2.12 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.mp4 2.11 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.mp4 2.11 MB
Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.mp4 2.1 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.mp4 2.1 MB
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.mp4 2.1 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.mp4 2.1 MB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.mp4 2.1 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.mp4 2.09 MB
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.mp4 2.09 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.mp4 2.09 MB
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.mp4 2.09 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.mp4 2.09 MB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.mp4 2.08 MB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.mp4 2.08 MB
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.mp4 2.08 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.mp4 2.08 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.mp4 2.07 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.mp4 2.07 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.mp4 2.07 MB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.mp4 2.07 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types-7DCw86WMpYo.mp4 2.07 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.mp4 2.07 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.mp4 2.06 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.mp4 2.06 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.mp4 2.06 MB
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.mp4 2.06 MB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.mp4 2.06 MB
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.mp4 2.06 MB
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.mp4 2.06 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.mp4 2.05 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.mp4 2.05 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.mp4 2.04 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.mp4 2.04 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.mp4 2.04 MB
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.mp4 2.04 MB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.mp4 2.03 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.mp4 2.03 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.mp4 2.03 MB
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.mp4 2.03 MB
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.mp4 2.03 MB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.mp4 2.03 MB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.mp4 2.03 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.mp4 2.03 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.mp4 2.02 MB
Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.mp4 2.02 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.mp4 2.02 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.mp4 2.02 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.mp4 2.02 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.mp4 2.01 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.mp4 2.01 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.mp4 2.01 MB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.mp4 2.01 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.mp4 2.01 MB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.mp4 2.01 MB
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.mp4 2.01 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.mp4 2 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.mp4 2 MB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.mp4 1.99 MB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.mp4 1.99 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.mp4 1.99 MB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.mp4 1.99 MB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.mp4 1.98 MB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.mp4 1.98 MB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.mp4 1.97 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.mp4 1.97 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.mp4 1.97 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.mp4 1.96 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.mp4 1.96 MB
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.mp4 1.96 MB
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.mp4 1.95 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.mp4 1.95 MB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.mp4 1.94 MB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.mp4 1.94 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.mp4 1.94 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.mp4 1.93 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.mp4 1.93 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.mp4 1.93 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.mp4 1.93 MB
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.mp4 1.93 MB
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.mp4 1.92 MB
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.mp4 1.92 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.mp4 1.92 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.mp4 1.91 MB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.mp4 1.91 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.mp4 1.91 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.mp4 1.91 MB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.mp4 1.91 MB
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.mp4 1.91 MB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.mp4 1.9 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.mp4 1.9 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.mp4 1.9 MB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.mp4 1.9 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.mp4 1.9 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.mp4 1.9 MB
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.mp4 1.89 MB
Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.mp4 1.89 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.mp4 1.89 MB
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.mp4 1.89 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.mp4 1.88 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.mp4 1.88 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.mp4 1.88 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.mp4 1.88 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.mp4 1.88 MB
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.mp4 1.88 MB
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.mp4 1.88 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.mp4 1.87 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame-N66_j0gxuhg.mp4 1.87 MB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.mp4 1.87 MB
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.mp4 1.87 MB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.mp4 1.86 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.mp4 1.86 MB
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.mp4 1.86 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.mp4 1.86 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.mp4 1.85 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.mp4 1.85 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.mp4 1.84 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.mp4 1.84 MB
Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.mp4 1.84 MB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.mp4 1.84 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.mp4 1.84 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.mp4 1.84 MB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.mp4 1.84 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.mp4 1.83 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.mp4 1.82 MB
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.mp4 1.82 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.mp4 1.82 MB
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.mp4 1.81 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.mp4 1.81 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.mp4 1.81 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.mp4 1.81 MB
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.mp4 1.81 MB
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.mp4 1.81 MB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.mp4 1.8 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.mp4 1.8 MB
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.mp4 1.8 MB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.mp4 1.79 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.mp4 1.79 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.mp4 1.79 MB
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.mp4 1.79 MB
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.mp4 1.79 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.mp4 1.79 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.mp4 1.78 MB
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.mp4 1.78 MB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.mp4 1.77 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.mp4 1.76 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.mp4 1.76 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.mp4 1.76 MB
Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.mp4 1.76 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.mp4 1.75 MB
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.mp4 1.75 MB
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.mp4 1.75 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.mp4 1.75 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.mp4 1.75 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.mp4 1.75 MB
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.mp4 1.75 MB
Part 12-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.mp4 1.75 MB
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.mp4 1.75 MB
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.mp4 1.74 MB
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.mp4 1.74 MB
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.mp4 1.74 MB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.mp4 1.74 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.mp4 1.73 MB
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.mp4 1.73 MB
Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.mp4 1.73 MB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.mp4 1.72 MB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.mp4 1.72 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.mp4 1.71 MB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.mp4 1.71 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.mp4 1.71 MB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.mp4 1.7 MB
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.mp4 1.7 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.mp4 1.69 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.mp4 1.69 MB
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.mp4 1.69 MB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.mp4 1.69 MB
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.mp4 1.69 MB
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.mp4 1.69 MB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.mp4 1.69 MB
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.mp4 1.68 MB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.mp4 1.68 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.mp4 1.68 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.mp4 1.68 MB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.mp4 1.67 MB
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.mp4 1.67 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.mp4 1.66 MB
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.mp4 1.66 MB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.mp4 1.65 MB
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.mp4 1.65 MB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.mp4 1.65 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.mp4 1.64 MB
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.mp4 1.64 MB
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.mp4 1.64 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.mp4 1.64 MB
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.mp4 1.64 MB
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.mp4 1.64 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.mp4 1.64 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.mp4 1.64 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.mp4 1.63 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.mp4 1.63 MB
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.mp4 1.62 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.mp4 1.62 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.mp4 1.62 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.mp4 1.62 MB
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.mp4 1.61 MB
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.mp4 1.61 MB
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.mp4 1.61 MB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.mp4 1.61 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.mp4 1.61 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.mp4 1.61 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.mp4 1.6 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.mp4 1.6 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.mp4 1.6 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.mp4 1.6 MB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.mp4 1.59 MB
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.mp4 1.59 MB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.mp4 1.59 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.mp4 1.59 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.mp4 1.59 MB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.mp4 1.59 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.mp4 1.59 MB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.mp4 1.59 MB
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.mp4 1.59 MB
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.mp4 1.58 MB
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.mp4 1.58 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.mp4 1.58 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.mp4 1.58 MB
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.mp4 1.58 MB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.mp4 1.57 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.mp4 1.57 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.mp4 1.57 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.mp4 1.57 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.mp4 1.57 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.mp4 1.57 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.mp4 1.56 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.mp4 1.56 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.mp4 1.55 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.mp4 1.55 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.mp4 1.55 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.mp4 1.55 MB
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.mp4 1.55 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.mp4 1.55 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.mp4 1.54 MB
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.mp4 1.54 MB
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.mp4 1.53 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.mp4 1.53 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.mp4 1.53 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.mp4 1.53 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.mp4 1.53 MB
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.mp4 1.53 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.mp4 1.53 MB
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.mp4 1.51 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.mp4 1.51 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.mp4 1.51 MB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.mp4 1.51 MB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.mp4 1.51 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.mp4 1.51 MB
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.mp4 1.51 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.mp4 1.51 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.mp4 1.5 MB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.mp4 1.5 MB
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.mp4 1.5 MB
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.mp4 1.49 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.mp4 1.49 MB
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.mp4 1.49 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.mp4 1.49 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.mp4 1.49 MB
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.mp4 1.49 MB
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.mp4 1.49 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.mp4 1.49 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.mp4 1.49 MB
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.mp4 1.48 MB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.mp4 1.48 MB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.mp4 1.48 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.mp4 1.48 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.mp4 1.48 MB
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.mp4 1.48 MB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.mp4 1.48 MB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.mp4 1.47 MB
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.mp4 1.47 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.mp4 1.47 MB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.mp4 1.47 MB
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.mp4 1.46 MB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.mp4 1.46 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.mp4 1.46 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.mp4 1.45 MB
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.mp4 1.45 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.mp4 1.45 MB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.mp4 1.44 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.mp4 1.44 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.mp4 1.44 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/img/set-up-reminder.gif 1.44 MB
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.mp4 1.43 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.mp4 1.43 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.mp4 1.43 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.mp4 1.43 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.mp4 1.43 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.mp4 1.43 MB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.mp4 1.43 MB
Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.mp4 1.43 MB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.mp4 1.43 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.mp4 1.43 MB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.mp4 1.42 MB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.mp4 1.42 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.mp4 1.42 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.mp4 1.41 MB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.mp4 1.41 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.mp4 1.41 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.mp4 1.41 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.mp4 1.41 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.mp4 1.41 MB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.mp4 1.41 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.mp4 1.41 MB
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.mp4 1.4 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.mp4 1.4 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.mp4 1.4 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.mp4 1.4 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.mp4 1.4 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.mp4 1.4 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.mp4 1.4 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.mp4 1.39 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.mp4 1.39 MB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.mp4 1.39 MB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.mp4 1.39 MB
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.mp4 1.39 MB
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.mp4 1.38 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.mp4 1.38 MB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.mp4 1.38 MB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.mp4 1.38 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.mp4 1.38 MB
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.mp4 1.37 MB
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.mp4 1.37 MB
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.mp4 1.37 MB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.mp4 1.37 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.mp4 1.36 MB
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.mp4 1.35 MB
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.mp4 1.34 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.mp4 1.34 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.mp4 1.34 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.mp4 1.33 MB
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.mp4 1.33 MB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.mp4 1.33 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.mp4 1.33 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.mp4 1.33 MB
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.mp4 1.33 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.mp4 1.32 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.mp4 1.32 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.mp4 1.32 MB
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.mp4 1.31 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.mp4 1.31 MB
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.mp4 1.31 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.mp4 1.31 MB
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.mp4 1.31 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.mp4 1.3 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.mp4 1.3 MB
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.mp4 1.3 MB
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.mp4 1.3 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.mp4 1.29 MB
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.mp4 1.29 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.mp4 1.29 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.mp4 1.29 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.mp4 1.29 MB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.mp4 1.29 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.mp4 1.29 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.mp4 1.28 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.mp4 1.28 MB
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.mp4 1.28 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.mp4 1.28 MB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.mp4 1.27 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.mp4 1.27 MB
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.mp4 1.26 MB
Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.mp4 1.25 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.mp4 1.25 MB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.mp4 1.25 MB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.mp4 1.25 MB
Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.mp4 1.25 MB
Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.mp4 1.24 MB
Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.mp4 1.24 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.mp4 1.24 MB
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.mp4 1.24 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.mp4 1.23 MB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.mp4 1.23 MB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.mp4 1.23 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.mp4 1.23 MB
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.mp4 1.23 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.mp4 1.22 MB
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.mp4 1.22 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.mp4 1.22 MB
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.mp4 1.22 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.mp4 1.22 MB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.mp4 1.22 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.mp4 1.22 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.mp4 1.21 MB
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.mp4 1.21 MB
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.mp4 1.21 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.mp4 1.21 MB
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.mp4 1.21 MB
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.mp4 1.21 MB
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.mp4 1.2 MB
Part 07-Module 01-Lesson 01_GitHub Review/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 10-Module 01-Lesson 02_LinkedIn Review/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 10-Module 01-Lesson 03_Udacity Professional Profile/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 12-Module 01-Lesson 05_Interview Practice/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 12-Module 02-Lesson 08_Technical Interview - Python/img/screen-shot-2017-10-31-at-1.06.42-pm.png 1.2 MB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/04. 02 Joining Tables-vSjKBMgW1Fw.mp4 1.2 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.mp4 1.2 MB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.mp4 1.19 MB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/img/760018543.gif 1.19 MB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.mp4 1.19 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.mp4 1.18 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.mp4 1.18 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.mp4 1.18 MB
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.mp4 1.18 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.mp4 1.18 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.mp4 1.18 MB
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.mp4 1.18 MB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.mp4 1.17 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.mp4 1.17 MB
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.mp4 1.17 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.mp4 1.17 MB
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.mp4 1.17 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.mp4 1.17 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.mp4 1.17 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.mp4 1.17 MB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.mp4 1.17 MB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.mp4 1.17 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.mp4 1.16 MB
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.mp4 1.16 MB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.mp4 1.16 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.mp4 1.16 MB
Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.mp4 1.16 MB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.mp4 1.16 MB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.mp4 1.16 MB
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.mp4 1.15 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.mp4 1.15 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.mp4 1.15 MB
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.mp4 1.15 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.mp4 1.14 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.mp4 1.14 MB
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.mp4 1.14 MB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.mp4 1.14 MB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.mp4 1.13 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.mp4 1.13 MB
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.mp4 1.13 MB
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.mp4 1.12 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.mp4 1.12 MB
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.mp4 1.12 MB
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.mp4 1.12 MB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.mp4 1.11 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.mp4 1.11 MB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.mp4 1.11 MB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.mp4 1.1 MB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.mp4 1.1 MB
Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.mp4 1.09 MB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.mp4 1.09 MB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.mp4 1.09 MB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.mp4 1.09 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.mp4 1.09 MB
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.mp4 1.08 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.mp4 1.08 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.mp4 1.08 MB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.mp4 1.08 MB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.mp4 1.07 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.mp4 1.07 MB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.mp4 1.07 MB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.mp4 1.07 MB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.mp4 1.07 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.mp4 1.07 MB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.mp4 1.07 MB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.mp4 1.06 MB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.mp4 1.06 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.mp4 1.06 MB
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.mp4 1.06 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.mp4 1.06 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.mp4 1.06 MB
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.mp4 1.06 MB
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.mp4 1.06 MB
Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.mp4 1.05 MB
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.mp4 1.05 MB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.mp4 1.04 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.mp4 1.04 MB
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.mp4 1.04 MB
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.mp4 1.04 MB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.mp4 1.04 MB
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.mp4 1.04 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.mp4 1.04 MB
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.mp4 1.04 MB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.mp4 1.03 MB
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.mp4 1.03 MB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.mp4 1.03 MB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/img/screenshot-2018-01-15-17.36.32.png 1.03 MB
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.mp4 1.03 MB
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.mp4 1.03 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.mp4 1.03 MB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.mp4 1.02 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.mp4 1.02 MB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.mp4 1.01 MB
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.mp4 1.01 MB
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.mp4 1.01 MB
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.mp4 1.01 MB
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.mp4 1.01 MB
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.mp4 1.01 MB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.mp4 1022.28 KB
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.mp4 1021.89 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-_yD3iz4bFhc.mp4 1019.5 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.mp4 1016.04 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/img/48713571.gif 1011.65 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.mp4 1010.76 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.mp4 1009.81 KB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.mp4 996.8 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.mp4 995.27 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.mp4 992.86 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.mp4 992.63 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.mp4 992.63 KB
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.mp4 991.73 KB
Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.mp4 991.68 KB
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.mp4 990.87 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/img/inner-outer.png 989.08 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/img/oblstsm-imgur.gif 988.07 KB
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.mp4 987.37 KB
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.mp4 985.36 KB
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.mp4 978.72 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.mp4 975.66 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.mp4 975.6 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.mp4 975.39 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.mp4 975.16 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -adqc5fF5B8Y.mp4 974.1 KB
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.mp4 973.33 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/img/d3-instructors.png 970.47 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/img/left-right.png 964.43 KB
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.mp4 960.33 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.mp4 956.6 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.mp4 954.56 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.mp4 953.68 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.mp4 953.17 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.mp4 949.3 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/img/5389263527.gif 942.76 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.mp4 938.03 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.mp4 931.75 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-3.48.20-pm.png 925.38 KB
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.mp4 920.84 KB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.mp4 919.5 KB
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.mp4 919.33 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.mp4 918.81 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.mp4 918.37 KB
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.mp4 918.37 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.mp4 915.72 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.mp4 915.12 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.mp4 914.34 KB
Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.mp4 912.58 KB
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.mp4 909.43 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.mp4 903.99 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t--ypzhIBAuvg.mp4 903.49 KB
Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.mp4 897.42 KB
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.mp4 896.74 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.mp4 893.3 KB
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.mp4 891.26 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.mp4 886.38 KB
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.mp4 886.38 KB
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.mp4 885.23 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.mp4 883.91 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.mp4 883.14 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2017-11-07-at-2.17.08-pm.png 882.6 KB
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.mp4 878.93 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.mp4 877.61 KB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.mp4 876.58 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.mp4 873.94 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.mp4 871.67 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.mp4 869.56 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.mp4 863.99 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.mp4 863.33 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.mp4 860.29 KB
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.mp4 853.58 KB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.mp4 846.57 KB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.mp4 842.63 KB
Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.mp4 840.45 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.mp4 836.26 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.mp4 834.73 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.mp4 832.68 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2017-11-07-at-2.18.27-pm.png 832.02 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.mp4 831.76 KB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.mp4 828.32 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.mp4 825.59 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.mp4 824.92 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.mp4 820.45 KB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.mp4 819.27 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.mp4 817.42 KB
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.mp4 817.3 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.mp4 814.35 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.mp4 809.93 KB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.mp4 805.54 KB
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.mp4 805.43 KB
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.mp4 803.69 KB
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.mp4 803.67 KB
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.mp4 800.53 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.mp4 798.61 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3011778732.gif 798.3 KB
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.mp4 797.83 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.mp4 794.35 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.mp4 792.74 KB
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.mp4 792.74 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.mp4 787.82 KB
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.mp4 787.82 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.mp4 787.51 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/img/726249228.gif 782.7 KB
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.mp4 782.02 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.mp4 781.88 KB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.mp4 780.78 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.mp4 778.92 KB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.mp4 776.82 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.mp4 774.95 KB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.mp4 774.95 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.mp4 771.83 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.mp4 770.56 KB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.mp4 770.56 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3013458575.gif 766.43 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3017968763.gif 765.91 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.mp4 765.63 KB
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.mp4 765.63 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.mp4 762.78 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/img/202900216.gif 761.33 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/img/groups-used-in-map.png 759.23 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/img/groups-used-in-map.png 759.23 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.mp4 758.41 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.mp4 757.48 KB
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.mp4 754.47 KB
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.mp4 753.05 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.mp4 752.85 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.mp4 751.89 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-ferT-sqV3A0.mp4 748.72 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.mp4 748.54 KB
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.mp4 747.61 KB
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.mp4 747.17 KB
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.mp4 745.32 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.mp4 743.92 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3013038717.gif 741.74 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3029558686.gif 738.48 KB
index.html 738.14 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.mp4 737.8 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3046518548.gif 736.99 KB
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.mp4 736.69 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.mp4 735.16 KB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.mp4 734.96 KB
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.mp4 734.83 KB
Part 09-Module 01-Lesson 02_R Basics/img/805108698.gif 732.66 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.mp4 727.9 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.mp4 727.9 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.mp4 727.7 KB
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.mp4 726.61 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.mp4 720.53 KB
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.mp4 720.53 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.mp4 719.39 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.mp4 715.26 KB
Part 07-Module 01-Lesson 01_GitHub Review/img/6509638772.gif 711.08 KB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.mp4 707.99 KB
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.mp4 702.49 KB
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.mp4 701.34 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3007818802.gif 696.79 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.mp4 694.91 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.mp4 693.68 KB
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.mp4 693.35 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.mp4 692.9 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.mp4 691.96 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.mp4 691.81 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/img/l1-worldcuptopscorers.png 688.82 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3000408954.gif 682.95 KB
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.mp4 682.5 KB
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.mp4 682.36 KB
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.mp4 677.09 KB
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.mp4 676.1 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3003048586.gif 675.79 KB
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.mp4 675.14 KB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.mp4 672.32 KB
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.mp4 672.27 KB
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.mp4 671.97 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/img/866348580.gif 671.32 KB
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.mp4 668.73 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3028758556.gif 663.44 KB
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.mp4 663.4 KB
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.mp4 661.88 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/img/92993674.gif 661.24 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.mp4 661.1 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/img/calculated-field-rows.png 659.97 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/img/calculated-field-rows.png 659.97 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.mp4 655.78 KB
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.mp4 650.53 KB
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.mp4 648.35 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.mp4 643.93 KB
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.mp4 642.74 KB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.mp4 642.43 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.mp4 640.71 KB
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.mp4 640.05 KB
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.mp4 639.69 KB
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.mp4 635 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/img/calculated-aggregation.png 629.89 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/img/calculated-aggregation.png 629.89 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-9TgKqnlta2U.mp4 627.78 KB
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.mp4 627.55 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.mp4 623.29 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.mp4 621.21 KB
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.mp4 621 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/img/calculated-aggregation-products.png 619.87 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/img/calculated-aggregation-products.png 619.87 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-9.43.05-am.png 618.06 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-1.33.46-pm.png 617.99 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.mp4 615.44 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-3.56.39-pm.png 610.41 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3018068594.gif 610.32 KB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.mp4 610.24 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-jNfrnjMn7dU.mp4 605.96 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/img/154863478.gif 605.23 KB
Part 11-Module 01-Lesson 02_Naive Bayes/img/3006519007.gif 604.07 KB
Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/img/144643881.gif 603.87 KB
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.mp4 603.29 KB
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.mp4 602.56 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3050828611.gif 600 KB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.mp4 599.63 KB
Part 11-Module 01-Lesson 04_Decision Trees/img/2952958620.gif 596.23 KB
Part 04-Module 01-Lesson 01_Anaconda/media/conda_default_install.mp4 595.3 KB
Part 16-Module 01-Lesson 01_Anaconda/media/conda_default_install.mp4 595.3 KB
Part 11-Module 01-Lesson 03_SVM/img/2949888602.gif 593.43 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-k7eajev401c.mp4 583.67 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/img/154863506.gif 583.49 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.mp4 582.78 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.mp4 579.06 KB
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.mp4 578.35 KB
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.mp4 577.97 KB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.mp4 569.35 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.mp4 569 KB
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.mp4 569 KB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.mp4 568.79 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/img/3037078563.gif 565.72 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.mp4 559.06 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.mp4 558.47 KB
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.mp4 558.47 KB
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.mp4 557.46 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-nG9l9ba7TrE.mp4 556.87 KB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.mp4 556.61 KB
Part 11-Module 01-Lesson 04_Decision Trees/img/2960808631.gif 556.05 KB
Part 11-Module 01-Lesson 03_SVM/img/2950698619.gif 555.55 KB
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.mp4 555.01 KB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.mp4 553.6 KB
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.mp4 546.12 KB
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/img/3884568702.gif 542.45 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-ylUUpaUfFEY.mp4 538.42 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/img/56480609.gif 536.97 KB
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Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.mp4 533.3 KB
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.mp4 533.2 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/img/56480616.gif 531.53 KB
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.mp4 528.9 KB
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.mp4 527.39 KB
Part 14-Module 01-Lesson 05_Analyzing Results/img/4091338676.gif 526.02 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/img/3849658626.gif 524.13 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.mp4 523 KB
Part 11-Module 01-Lesson 02_Naive Bayes/img/3060688537.gif 521.74 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2018-11-19-at-11.32.05-am.png 521.11 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.mp4 519.23 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.mp4 519.05 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/img/3838118725.gif 518.68 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/img/56480615.gif 518.66 KB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.mp4 518.43 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/img/81190229.gif 517.21 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.mp4 516.06 KB
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/img/56480610.gif 514.65 KB
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Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.mp4 513.65 KB
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Part 21-Module 01-Lesson 01_Why Python Programming/img/screen-shot-2018-03-19-at-2.30.59-pm.png 507.42 KB
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.mp4 506.06 KB
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Part 16-Module 02-Lesson 01_The Data Analysis Process/img/5.dap-quiz-img5.png 503.31 KB
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.mp4 502.72 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.mp4 502.09 KB
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.mp4 502.09 KB
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/img/5393474438.gif 497.27 KB
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Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.mp4 478.69 KB
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Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.mp4 473.01 KB
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Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.mp4 470.59 KB
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/img/calculated-profit-per-item.png 467.59 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/img/calculated-profit-per-item.png 467.59 KB
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Part 06-Module 01-Lesson 03_Analyzing Data/10. Using match and project.html 15.55 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/07. Exploring Users.html 15.55 KB
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Part 18-Module 02-Lesson 01_Gathering Data/18. Mashup APIs, Downloading Files Programmatically, JSON.html 15.43 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance.html 15.33 KB
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Part 17-Module 01-Lesson 16_Logistic Regression/08. Notebook + Quiz Interpret Results.html 15.31 KB
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/10. Quizzes On Scatter Plots.html 15.25 KB
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/19. Quiz Aggregations.html 15.17 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Boolean Expressions for Conditions.html 15.16 KB
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Part 18-Module 02-Lesson 01_Gathering Data/22. Relational Database Structure.html 15.08 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/27. Quiz + Text Recap Next Steps.html 15.08 KB
Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3.html 15.06 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/13. Quiz Types of Errors - Part III.html 15.06 KB
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Part 19-Module 01-Lesson 02_Design/20. Quizzes on Data Story Telling.html 15.03 KB
Part 09-Module 02-Lesson 01_Explore and Summarize Data/Project Rubric - Explore and Summarize Data.html 14.93 KB
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Part 06-Module 01-Lesson 03_Analyzing Data/14. Using push.html 14.87 KB
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Part 17-Module 01-Lesson 13_Case Study AB tests/17. Quiz Difficulties in AB Testing.html 14.75 KB
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Video + Quiz Write Your First Subquery.html 14.66 KB
Part 16-Module 03-Lesson 01_Basic SQL/12. Your First Queries in SQL Workspace.html 14.65 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/24. Quiz Shape and Outliers (Visuals).html 14.6 KB
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files.html 14.55 KB
Part 17-Module 01-Lesson 16_Logistic Regression/05. Notebook + Quiz Fitting Logistic Regression in Python.html 14.55 KB
Part 17-Module 01-Lesson 14_Regression/11. Quiz What Defines A Line - Notation Quiz.html 14.52 KB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces).html 14.52 KB
Part 21-Module 01-Lesson 05_Scripting/04. [For Windows] Configuring Git Bash to Run Python.html 14.49 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code.html 14.49 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Groups and Sets.html 14.47 KB
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Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy.html 14.39 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/24. Text Marks Filters I.html 14.38 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/23. Quiz Lists and Membership Operators.html 14.38 KB
Part 06-Module 01-Lesson 03_Analyzing Data/05. Using group.html 14.37 KB
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/16. [Optional] Text Linear Model Assumptions.html 14.32 KB
Part 18-Module 03-Lesson 01_Assessing Data/05. Unclean Data Dirty vs. Messy 2.html 14.3 KB
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Part 16-Module 03-Lesson 01_Basic SQL/06. Video Why SQL.html 14.25 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process.html 14.18 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Quiz Gather (Unzip File).html 14.17 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/21. Quiz What is a p-value Anyway.html 14.14 KB
Part 17-Module 01-Lesson 16_Logistic Regression/30. Notebook + Quiz Model Diagnostics.html 14.06 KB
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample.html 13.87 KB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts.html 13.85 KB
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/04. Text Outline of Topics Covered.html 13.78 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/15. Homework 1 Final Quiz on Measures Spread.html 13.78 KB
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Part 21-Module 01-Lesson 02_Data Types and Operators/34. Quiz More With Dictionaries.html 13.72 KB
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/19. Notebook + Quiz Multicollinearity VIFs.html 13.71 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate.html 13.7 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/06. Getting Data.html 13.7 KB
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies.html 13.64 KB
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate.html 13.61 KB
Part 15-Module 01-Lesson 02_Design Principles/18. Design integrity.html 13.6 KB
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Part 21-Module 01-Lesson 03_Control Flow/16. Building Dictionaries.html 13.57 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/06. Aggregation and granularity.html 13.56 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles.html 13.5 KB
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Part 11-Module 01-Lesson 04_Decision Trees/09. Decision Tree Accuracy.html 13.44 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center.html 13.41 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. Sheet interface.html 13.41 KB
Part 16-Module 03-Lesson 01_Basic SQL/14. Formatting Best Practices.html 13.39 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.pt-BR.vtt 13.37 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/10. Quiz Types of Errors - Part II(a).html 13.37 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/03. Data in NumPy.html 13.36 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/25. Dot Notation.html 13.33 KB
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Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types.html 13.27 KB
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Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera.html 13.24 KB
Part 12-Module 02-Lesson 06_Graphs/08. Graph Representation Practice.html 13.24 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/Project Rubric - Resume Review Project (Career Change).html 13.23 KB
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Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression.html 13.21 KB
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Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color.html 13.19 KB
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3.html 13.16 KB
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Part 06-Module 01-Lesson 01_Working with MongoDB/10. Finding Porsche.html 13.12 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods.html 13.11 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/14. [Optional] Notebook + Quiz Other Encodings.html 13.09 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/32. Solutions CASE.html 13.08 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game.html 13.07 KB
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Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/08. Scales and Multiple Histograms.html 13.05 KB
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Part 06-Module 01-Lesson 01_Working with MongoDB/23. Using $in Operator.html 12.96 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Quiz Clean (Code 2).html 12.84 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/16. Reader Bias.html 12.76 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/07. Template and Software.html 12.73 KB
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Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases.html 12.71 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/32. Text Small Multiples Dual Axis.html 12.71 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/10. Dummy Variables.html 12.69 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__.html 12.67 KB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files in Python.html 12.67 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps.html 12.67 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Quiz Gather (Download).html 12.66 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings.html 12.66 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/20. String Methods.html 12.66 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/10. Exploration vs Explanation.html 12.65 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/21. Notebook + Quiz Central Limit Theorem - Part III.html 12.65 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/11. Subquery Solution Video-Y6S3S0LsMrw.en.vtt 12.65 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited.html 12.63 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/44. Text Table Calculations.html 12.63 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths.html 12.62 KB
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/07. Quiz More On Subqueries.html 12.58 KB
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Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2.html 12.56 KB
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/26. Text Descriptive Statistics Summary .html 12.54 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/12. Quizzes UNION.html 12.53 KB
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Part 21-Module 01-Lesson 02_Data Types and Operators/03. Quiz Arithmetic Operators.html 12.51 KB
Part 10-Module 01-Lesson 02_LinkedIn Review/Project Rubric - LinkedIn Profile Review Project.html 12.5 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples.html 12.48 KB
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Part 16-Module 03-Lesson 01_Basic SQL/48. Solutions OR.html 10.69 KB
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color.html 10.5 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed.html 10.42 KB
Part 11-Module 01-Lesson 13_PCA/35. How Many PCs to Use.html 10.42 KB
Part 16-Module 03-Lesson 01_Basic SQL/09. Video Types of Statements.html 10.42 KB
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic.html 9.83 KB
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule.html 9.83 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values.html 9.83 KB
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means.html 9.83 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/02. Course Outline.html 9.83 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/21. Solutions DISTINCT.html 9.83 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals.html 9.83 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/04. Setting Up Your System.html 9.82 KB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn.html 9.82 KB
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees.html 9.82 KB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy.html 9.82 KB
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR.html 9.82 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean).html 9.82 KB
Part 16-Module 03-Lesson 01_Basic SQL/02. Video The Parch Posey Database.html 9.82 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/08. Magic keywords.html 9.82 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/08. Magic keywords.html 9.82 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. Other Things to Consider - How Do CIs and HTs Compare.html 9.82 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting.html 9.82 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. Video How This Lesson Is Structured.html 9.81 KB
Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup.html 9.81 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Video Small Multiples Dual Axis.html 9.81 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means.html 9.81 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size.html 9.81 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size.html 9.81 KB
Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations.html 9.81 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data.html 9.81 KB
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD).html 9.8 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans().html 9.8 KB
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Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Text Installing Tableau.html 9.8 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Video Measures of Center (Mean).html 9.8 KB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1.html 9.79 KB
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Part 11-Module 01-Lesson 04_Decision Trees/41. Accuracy Using 1 of Features.html 9.79 KB
Part 15-Module 01-Lesson 02_Design Principles/14. Practical Rules for Using Color.html 9.79 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/04. Asking Questions.html 9.79 KB
Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure.html 9.78 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d.html 9.78 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Video Introduction.html 9.78 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What.html 9.78 KB
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory.html 9.77 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory.html 9.77 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean.html 9.77 KB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day.html 9.76 KB
Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/05. Cheaper Diamonds.html 9.76 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10.html 9.76 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results.html 9.76 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results.html 9.75 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/26. Video DATE Functions II.html 9.75 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From.html 9.75 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test.html 9.75 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/10. Fixing Data Types Pt 2.html 9.75 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001.html 9.75 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05.html 9.74 KB
Part 16-Module 03-Lesson 01_Basic SQL/01. Video SQL Introduction.html 9.74 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI.html 9.74 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01.html 9.73 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d.html 9.73 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely.html 9.73 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel.html 9.73 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Video Table Calculations.html 9.72 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject.html 9.72 KB
Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines.html 9.72 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind.html 9.72 KB
Part 11-Module 01-Lesson 12_Feature Selection/27. Identify the Most Powerful Features.html 9.72 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/13. Metric - Completion Rate.html 9.72 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/10. Metric - Enrollment Rate.html 9.72 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value.html 9.72 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/06. Quiz JOINs with Comparison Operators.html 9.72 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind.html 9.72 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Video Marks Filters.html 9.72 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Video Calculated Fields.html 9.72 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null.html 9.71 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Video The Shape For Data In The World.html 9.71 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data.html 9.71 KB
Part 05-Module 03-Lesson 01_Wrangle OpenStreetMap Data/Project Description - Wrangle OpenStreetMap Data.html 9.71 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys.html 9.71 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. Video What is Tableau.html 9.7 KB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2.html 9.7 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. Video What's Next.html 9.7 KB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores.html 9.7 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Video Groups Sets.html 9.7 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions.html 9.7 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Video Two Useful Theorems - Central Limit Theorem.html 9.7 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions in Hypothesis Testing.html 9.7 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure.html 9.69 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/04. Setting Up Your Programming Environment.html 9.69 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/35. Mixing Data Sources (optional).html 9.69 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes.html 9.68 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-XTS6m5_3fdU.ar.vtt 9.68 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Video Notation for the Mean.html 9.68 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Video Aggregations.html 9.68 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price.html 9.68 KB
Part 11-Module 01-Lesson 12_Feature Selection/25. Number of Features and Overfitting.html 9.68 KB
Part 11-Module 01-Lesson 03_SVM/34. Accuracy after Optimizing C.html 9.67 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/11. Data Types (Continuous vs. Discrete).html 9.67 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Video Hierarchies.html 9.67 KB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, Other Tools.html 9.67 KB
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule.html 9.67 KB
Part 16-Module 03-Lesson 02_SQL Joins/06. Text ERD Reminder.html 9.66 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Video Worksheets.html 9.66 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots.html 9.66 KB
Part 17-Module 01-Lesson 14_Regression/12. Quiz What Defines A Line - Line Basics Quiz.html 9.66 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction.html 9.66 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations.html 9.66 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major.html 9.65 KB
Part 12-Module 02-Lesson 05_Trees/11. Binary Tree Practice.html 9.65 KB
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day.html 9.65 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/11. Quiz MIN, MAX, AVG.html 9.65 KB
Part 11-Module 01-Lesson 09_Clustering/24. Clustering Changes.html 9.65 KB
Part 17-Module 01-Lesson 04_Probability/14. One Head 2.html 9.65 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/15. Conclusions Using Query.html 9.64 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Video Show Me.html 9.64 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind.html 9.63 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind.html 9.63 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. Video GROUP BY.html 9.63 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Video Shape and Outliers.html 9.62 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/27. Quiz DATE Functions.html 9.62 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/05. Text Descriptive vs. Inferential Statistics.html 9.62 KB
Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1.html 9.62 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2.html 9.61 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas.html 9.61 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/06. Promoting Rock Music.html 9.61 KB
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD.html 9.61 KB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words.html 9.61 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets.html 9.61 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. Video + Text First Aggregation - COUNT.html 9.61 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. Video Measures of Center (Median).html 9.6 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. Video What are Measures of Spread.html 9.6 KB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope.html 9.6 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision.html 9.59 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Video Why Would We Want to Split Data Into Separate Tables.html 9.58 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes.html 9.58 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure.html 9.58 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/15. Solution Strings.html 9.58 KB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results.html 9.58 KB
Part 11-Module 01-Lesson 12_Feature Selection/06. Example Buggy Feature.html 9.57 KB
Part 16-Module 03-Lesson 02_SQL Joins/21. Text Recap Looking Ahead.html 9.57 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Introduction.html 9.57 KB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds.html 9.57 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis.html 9.56 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis.html 9.56 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/44. Metrics for Your POI Identifier.html 9.56 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/04. 11. Which Are Not Constructs.html 9.56 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean.html 9.56 KB
Part 11-Module 01-Lesson 03_SVM/33. Optimize C Parameter.html 9.56 KB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection.html 9.55 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/07. Filter, Drop Nulls, Dedupe.html 9.55 KB
Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn.html 9.55 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price.html 9.55 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. D3 Chaining Syntax.html 9.55 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference.html 9.54 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R.html 9.54 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. Create a Radius Scale.html 9.54 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size.html 9.54 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average.html 9.54 KB
Part 21-Module 01-Lesson 03_Control Flow/33. Solution List Comprehensions.html 9.53 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average.html 9.53 KB
Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis.html 9.53 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data.html 9.53 KB
Part 21-Module 01-Lesson 03_Control Flow/06. Solution Conditional Statements.html 9.52 KB
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Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/07. Text General Notes for Building Stories.html 9.52 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/19. Quiz On Visual Encodings.html 9.52 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. Video When Does the Central Limit Theorem Not Work.html 9.52 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/04. Recursion-_aI2Jch6Epk.en-US.vtt 9.51 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts.html 9.5 KB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R.html 9.5 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/15. Quiz COALESCE.html 9.5 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude.html 9.5 KB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250.html 9.49 KB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean.html 9.49 KB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size.html 9.49 KB
Part 21-Module 01-Lesson 04_Functions/15. [Optional] Quiz Iterators and Generators.html 9.49 KB
Part 07-Module 01-Lesson 01_GitHub Review/Project Description - Optimize Your GitHub Profile.html 9.49 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. D3 Scale Syntax.html 9.48 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.en-US.vtt 9.48 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution.html 9.47 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median.html 9.47 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/28. Data Wrangling Summary.html 9.47 KB
Part 18-Module 03-Lesson 01_Assessing Data/09. Quality Visual Assessment 1.html 9.47 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/12. Adjustments - price vs. volume.html 9.46 KB
Part 21-Module 01-Lesson 05_Scripting/05. Running a Python Script.html 9.46 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up.html 9.46 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect.html 9.46 KB
Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects.html 9.46 KB
Part 21-Module 01-Lesson 04_Functions/03. Quiz Defining Functions.html 9.46 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution.html 9.46 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo.html 9.45 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/07. Quiz SUM.html 9.45 KB
Part 21-Module 01-Lesson 04_Functions/12. Quiz Lambda Expressions.html 9.45 KB
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval.html 9.45 KB
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues.html 9.45 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/10. Appending Data (cont.).html 9.45 KB
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3.html 9.45 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo.html 9.45 KB
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.ar.vtt 9.44 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day.html 9.44 KB
Part 16-Module 03-Lesson 02_SQL Joins/12. Solutions JOIN Questions Part I.html 9.44 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/06. Markdown cells.html 9.44 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/06. Markdown cells.html 9.44 KB
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Part 11-Module 01-Lesson 03_SVM/30. A Smaller Training Set.html 9.43 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate.html 9.43 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables.html 9.43 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.ja.vtt 9.43 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables.html 9.43 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/26. Wrangling vs. EDA vs. ETL.html 9.42 KB
Part 04-Module 03-Lesson 01_Investigate a Dataset/02. Project Details.html 9.42 KB
Part 05-Module 02-Lesson 02_Problem Set Data and Tables/09. Interpreting Schema.html 9.42 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision.html 9.41 KB
Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/07. 18. Cell Phone Law Difference Scores.html 9.4 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/14. Project Description.html 9.4 KB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags.html 9.4 KB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI.html 9.4 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format.html 9.4 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment.html 9.4 KB
Part 05-Module 02-Lesson 02_Problem Set Data and Tables/05. Welcome to SQLite!.html 9.4 KB
Part 11-Module 01-Lesson 12_Feature Selection/29. Remove, Repeat.html 9.4 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/03. Quiz FULL OUTER JOIN.html 9.39 KB
Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint.html 9.39 KB
Part 18-Module 02-Lesson 01_Gathering Data/10. HTML Files In Python 2-3caDGTxcoCw.ar.vtt 9.39 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Video Histograms.html 9.39 KB
Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger.html 9.39 KB
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Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Video Calculating the p-value.html 9.38 KB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting with Raw Input.html 9.37 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/16. Video GROUP BY Part II.html 9.37 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words.html 9.37 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2.html 9.37 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score.html 9.36 KB
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI.html 9.36 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games.html 9.36 KB
Part 15-Module 01-Lesson 02_Design Principles/17. Bad Visual Quizzes.html 9.36 KB
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Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall.html 9.35 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text.html 9.34 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/11. Efficiency Practice.html 9.34 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier.html 9.34 KB
Part 09-Module 02-Lesson 01_Explore and Summarize Data/Project Description - Explore and Summarize Data.html 9.34 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Video Window Functions 1.html 9.33 KB
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Part 04-Module 01-Lesson 02_Jupyter notebooks/04. Notebook interface.html 9.32 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/04. Notebook interface.html 9.32 KB
Part 17-Module 01-Lesson 14_Regression/05. Quiz Linear Regression Language.html 9.32 KB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds.html 9.32 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries.html 9.32 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/33. Solution Dictionaries and Identity Operators.html 9.32 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. CSS Class Selectors.html 9.32 KB
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio.html 9.32 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. Changing the Title.html 9.32 KB
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Video Standard Deviation Calculation.html 9.31 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample.html 9.31 KB
Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients.html 9.3 KB
Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Phase II Clinical Trial Data.html 9.3 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/04. Solution Arithmetic Operators.html 9.3 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/15. Correct Interpretations of Confidence Intervals.html 9.29 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/12. Solution Booleans, Comparison and Logical Operators.html 9.29 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/15. Quiz Analyzing Multiple Metrics.html 9.29 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/05. Screencast + Text How Does MLR Work.html 9.29 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/17. Quiz Comparing a Row to Previous Row.html 9.29 KB
Part 10-Module 01-Lesson 02_LinkedIn Review/01. Using LinkedIn.html 9.29 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan.html 9.29 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs.html 9.29 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not.html 9.29 KB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses.html 9.29 KB
Part 17-Module 01-Lesson 16_Logistic Regression/09. Video Model Diagnostics + Performance Metrics.html 9.29 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not.html 9.29 KB
Part 21-Module 01-Lesson 03_Control Flow/19. Solution Iterating Through Dictionaries.html 9.28 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values.html 9.28 KB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text.html 9.28 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R.html 9.28 KB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At.html 9.28 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/09. Mode of Categorical Data.html 9.28 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable.html 9.28 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/29. Missing POIs 1 (optional).html 9.27 KB
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Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation.html 9.27 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test.html 9.27 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/09. Text Dummy Variables.html 9.27 KB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable.html 9.26 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. Examples.html 9.26 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values.html 9.26 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset.html 9.26 KB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters.html 9.26 KB
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine.html 9.26 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning.html 9.25 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/37. Solution Compound Data Structions.html 9.25 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier.html 9.25 KB
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Part 18-Module 04-Lesson 01_Cleaning Data/07. Quiz and Solution Notebooks.html 9.24 KB
Part 07-Module 01-Lesson 01_GitHub Review/Project Rubric - Optimize Your GitHub Profile.html 9.24 KB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/04. Building a Dashboard.html 9.23 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean.html 9.23 KB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types.html 9.22 KB
Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation.html 9.21 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Video The Background of Bootstrapping.html 9.21 KB
Part 12-Module 01-Lesson 05_Interview Practice/Project Rubric - Interview Practice (Data Analyst).html 9.2 KB
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Part 11-Module 01-Lesson 12_Feature Selection/28. Use TfIdf to Get the Most Important Word.html 9.2 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Video Dummy Variables.html 9.2 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Video Measures of Center (Mode).html 9.19 KB
Part 17-Module 01-Lesson 14_Regression/03. Quiz Machine Learning Big Picture.html 9.19 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety.html 9.19 KB
Part 11-Module 01-Lesson 03_SVM/38. Final Thoughts on Deploying SVMs.html 9.19 KB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation.html 9.19 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic.html 9.18 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/10. Transposes in NumPy.html 9.18 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage.html 9.18 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment.html 9.18 KB
Part 05-Module 02-Lesson 02_Problem Set Data and Tables/01. WARM UP - Chinook Query Playground.html 9.18 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/14. Quiz WITH.html 9.18 KB
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Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/05. Element-wise Operations in NumPy.html 9.17 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution.html 9.17 KB
Part 13-Module 02-Lesson 01_Make Effective Data Visualization/01. Project Overview.html 9.17 KB
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account.html 9.17 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values.html 9.17 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Video Multiple Linear Regression.html 9.16 KB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA.html 9.16 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Video Introduction to Sampling Distributions Part III.html 9.16 KB
Part 11-Module 01-Lesson 03_SVM/28. SVM Author ID Accuracy.html 9.16 KB
Part 11-Module 01-Lesson 03_SVM/35. Optimized RBF vs. Linear SVM Accuracy.html 9.16 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling.html 9.15 KB
Part 11-Module 01-Lesson 13_PCA/26. Applying PCA to Real Data.html 9.15 KB
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. Video Better Way.html 9.14 KB
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/11. Fixing Data Types Pt 3.html 9.14 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins.html 9.14 KB
Part 12-Module 02-Lesson 05_Trees/14. BST Practice.html 9.14 KB
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization.html 9.13 KB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error.html 9.13 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/17. Summary Metrics Example.html 9.13 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts.html 9.13 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/05. Good vs. Bad Data Viz Examples.html 9.13 KB
Part 21-Module 01-Lesson 03_Control Flow/22. Solution While Loops Practice.html 9.12 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/01. D3 version notice.html 9.12 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Video NULLs and Aggregation.html 9.12 KB
Part 21-Module 01-Lesson 04_Functions/14. [Optional] Iterators and Generators.html 9.12 KB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands).html 9.12 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion.html 9.12 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why use data visualization.html 9.12 KB
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2.html 9.11 KB
Part 15-Module 01-Lesson 02_Design Principles/05. Chart Relationships 2.html 9.11 KB
Part 17-Module 01-Lesson 14_Regression/14. Text The Regression Closed Form Solution.html 9.11 KB
Part 13-Module 01-Lesson 07_Narrative Structures/index.html 9.11 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis.html 9.11 KB
Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type.html 9.11 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting.html 9.11 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. Video LEFT and RIGHT JOINs.html 9.1 KB
Part 11-Module 01-Lesson 13_PCA/29. When to Use PCA.html 9.1 KB
Part 11-Module 01-Lesson 13_PCA/31. Eigenfaces Code.html 9.1 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram.html 9.09 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic.html 9.09 KB
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Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Video Multiple Linear Regression Model Results.html 9.09 KB
Part 19-Module 01-Lesson 02_Design/09. Design Integrity.html 9.08 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/05. Recursion Practice.html 9.08 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. Video What if We Only Want One Number.html 9.08 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI.html 9.08 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/15. Merging Datasets.html 9.08 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing.html 9.07 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/08. 10. Which Are Constructs.html 9.07 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions.html 9.07 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity.html 9.07 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. Video Weekdays vs. Weekends What is the Difference.html 9.07 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/16. Data Types.html 9.06 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results.html 9.06 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/06. Python The Basics.html 9.06 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/30. Further Study.html 9.06 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Video Why the Standard Deviation.html 9.06 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/32. Missing POIs 4 (optional).html 9.05 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency.html 9.05 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/05. Adjustments - price vs. depth.html 9.05 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart.html 9.05 KB
Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart.html 9.05 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/25. Video DATE Functions.html 9.05 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation.html 9.05 KB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization.html 9.04 KB
Part 16-Module 02-Lesson 04_Programming Workflow for Data Analysis/02. Analyzing with IPython.html 9.04 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Video Summary.html 9.04 KB
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1.html 9.04 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2.html 9.04 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2.html 9.04 KB
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size.html 9.04 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/18. Solution Type and Type Conversion.html 9.04 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score.html 9.03 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Video Data Types (Continuous vs. Discrete).html 9.03 KB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers.html 9.03 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization.html 9.03 KB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programmatic Assessment.html 9.03 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis.html 9.03 KB
Part 11-Module 01-Lesson 12_Feature Selection/23. Overfitting a Decision Tree 1.html 9.03 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line.html 9.02 KB
Part 11-Module 01-Lesson 03_SVM/32. Deploy an RBF Kernel.html 9.02 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision.html 9.02 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Video Percentiles.html 9.02 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/26. Up and Down the Visualization Spectrum.html 9 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Write the Body.html 9 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values.html 9 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/15. Mini-Project 1 RAW Visualization.html 9 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/05. Text Subquery Formatting.html 9 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price.html 8.99 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/09. Video MIN MAX.html 8.99 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship.html 8.99 KB
Part 21-Module 01-Lesson 03_Control Flow/01. Introduction.html 8.99 KB
Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Phase II Clinical Trial Data.html 8.99 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error.html 8.99 KB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple.html 8.99 KB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature.html 8.98 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/19. Video DISTINCT.html 8.98 KB
Part 11-Module 01-Lesson 03_SVM/37. How Many Chris Emails Predicted.html 8.98 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/37. Increase Engagement.html 8.96 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/03. Python Dictionaries.html 8.96 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/13. Size of the Enron Dataset.html 8.96 KB
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score.html 8.95 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise.html 8.95 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study-ahaxt6UKxQw.zh-CN.vtt 8.94 KB
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma.html 8.94 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate.html 8.94 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/09. price vs. volume.html 8.94 KB
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video.html 8.94 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings.html 8.93 KB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields.html 8.93 KB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary.html 8.93 KB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-i3RTW83wI1Q.pt-BR.vtt 8.93 KB
Part 15-Module 01-Lesson 02_Design Principles/02. Common Chart Types.html 8.92 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/20. Quiz DISTINCT.html 8.92 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript.html 8.92 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs.html 8.92 KB
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Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200.html 8.92 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210.html 8.92 KB
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Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing vs. Exploring.html 8.92 KB
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression.html 8.92 KB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude.html 8.92 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON.html 8.91 KB
Part 09-Module 02-Lesson 01_Explore and Summarize Data/01. Project Overview.html 8.91 KB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis.html 8.91 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction.html 8.91 KB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD.html 8.9 KB
Part 11-Module 01-Lesson 09_Clustering/12. Sklearn-3zHUAXcoZ7c.ar.vtt 8.9 KB
Part 17-Module 01-Lesson 16_Logistic Regression/31. Video Final Thoughts On Shifting to Machine Learning.html 8.9 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/17. Screencast Multicollinearity VIFs.html 8.9 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet.html 8.9 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking.html 8.9 KB
Part 15-Module 01-Lesson 02_Design Principles/img/sequential2.png 8.9 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI.html 8.89 KB
Part 21-Module 01-Lesson 03_Control Flow/12. Solution For Loops Practice.html 8.89 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/10. Video Traditional Confidence Intervals.html 8.89 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions.html 8.89 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs.html 8.89 KB
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie.html 8.89 KB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format.html 8.89 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations.html 8.89 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic.html 8.89 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion.html 8.88 KB
Part 13-Module 01-Lesson 05_Dimple.js/03. World Cup Sketch.html 8.88 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/05. Best Customer Emails.html 8.88 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20.html 8.88 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/10. Video AVG.html 8.88 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=.html 8.88 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic.html 8.88 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/15. Finding POIs in the Enron Data.html 8.88 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/10. Techniques to Gather Additional Data.html 8.87 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals.html 8.87 KB
Part 12-Module 01-Lesson 05_Interview Practice/02. Quiz Analyzing an Interview.html 8.87 KB
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM.html 8.87 KB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn.html 8.87 KB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs.html 8.87 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2-siuolDaB4eU.en.vtt 8.87 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/05. Walkthrough and Dataset.html 8.87 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/11. Target Population-HO1Doq8PiCI.ar.vtt 8.86 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages.html 8.86 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare.html 8.86 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1.html 8.85 KB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick.html 8.85 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types of Errors - Part I.html 8.85 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/33. Missing POIs 5 (optional).html 8.85 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical.html 8.85 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error.html 8.85 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. Video CASE Aggregations.html 8.85 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/27. Dealing with Unfilled Features.html 8.84 KB
Part 17-Module 01-Lesson 16_Logistic Regression/04. Video Fitting Logistic Regression in Python.html 8.84 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/03. A Definition and An Analogy.html 8.84 KB
Part 21-Module 01-Lesson 05_Scripting/19. Solution Reading and Writing Files.html 8.84 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/16. How Many POIs Exist.html 8.83 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/12. Next Steps.html 8.83 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table.html 8.83 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset.html 8.83 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price.html 8.83 KB
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3.html 8.83 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2-siuolDaB4eU.pt-BR.vtt 8.83 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/34. Missing POIs 6 (optional).html 8.83 KB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2.html 8.83 KB
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2.html 8.82 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error.html 8.82 KB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating.html 8.82 KB
Part 21-Module 01-Lesson 03_Control Flow/27. Solution Break, Continue.html 8.82 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region.html 8.82 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/12. Datasets and Questions Mini-Project.html 8.82 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/31. Missing POIs 3 (optional).html 8.81 KB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Video (ScreenCast) Interpret Results - Part II.html 8.81 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data.html 8.81 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing.html 8.81 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Video Why are Sampling Distributions Important.html 8.81 KB
Part 18-Module 03-Lesson 01_Assessing Data/06. Assessment Types vs. Steps.html 8.81 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1.html 8.81 KB
Part 18-Module 02-Lesson 01_Gathering Data/02. Lesson Outline.html 8.81 KB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array.html 8.8 KB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram.html 8.8 KB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters.html 8.8 KB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter.html 8.8 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.pt-BR.vtt 8.8 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant.html 8.8 KB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll.html 8.8 KB
Part 11-Module 01-Lesson 14_Validation/12. GridSearchCV in sklearn.html 8.8 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/17. Problems with Incomplete Data.html 8.79 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic.html 8.79 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/06. Video SUM.html 8.79 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/12. 16. Which Are Hypotheses.html 8.79 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features.html 8.79 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout.html 8.79 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1.html 8.79 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=.html 8.79 KB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data.html 8.79 KB
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5.html 8.79 KB
Part 18-Module 02-Lesson 01_Gathering Data/04. Navigating Your Working Directory and File IO.html 8.78 KB
Part 17-Module 01-Lesson 16_Logistic Regression/01. Video Introduction.html 8.78 KB
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors.html 8.78 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/14. Scatter Plot wMultiple Dimensions.html 8.78 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning.html 8.78 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia.html 8.78 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients.html 8.77 KB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Video Fitting Logistic Regression.html 8.77 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/20. Query the Dataset 3.html 8.77 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data.html 8.77 KB
Part 05-Module 03-Lesson 01_Wrangle OpenStreetMap Data/01. Project Overview.html 8.77 KB
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means.html 8.76 KB
Part 17-Module 01-Lesson 04_Probability/13. One Head 1.html 8.76 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/10. String Keys Practice.html 8.76 KB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability.html 8.76 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes.html 8.76 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.en.vtt 8.76 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age.html 8.76 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60.html 8.75 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/10. Quiz Subquery Mania.html 8.75 KB
Part 11-Module 01-Lesson 12_Feature Selection/09. Univariate Feature Selection.html 8.75 KB
Part 11-Module 01-Lesson 12_Feature Selection/31. Accuracy of the Overfit Tree.html 8.75 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/04. Downloading Enron Data.html 8.75 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/15. Solutions Aliases for Multiple Window Functions.html 8.75 KB
Part 16-Module 03-Lesson 02_SQL Joins/10. Video Alias.html 8.75 KB
Part 04-Module 01-Lesson 01_Anaconda/05. Managing environments.html 8.75 KB
Part 16-Module 01-Lesson 01_Anaconda/05. Managing environments.html 8.75 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. Video CAST.html 8.75 KB
Part 10-Module 01-Lesson 03_Udacity Professional Profile/03. Customizing Your Profile.html 8.75 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music.html 8.75 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60.html 8.74 KB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2.html 8.74 KB
Part 21-Module 01-Lesson 04_Functions/08. Documentation.html 8.74 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements.html 8.74 KB
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin.html 8.74 KB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Video Interpreting Results - Part I.html 8.74 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM.html 8.74 KB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts.html 8.74 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value.html 8.73 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/22. Solutions Percentiles.html 8.73 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Video Data Types (Quantitative vs. Categorical).html 8.73 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age.html 8.73 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC.html 8.73 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance.html 8.73 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2.html 8.72 KB
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2.html 8.72 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution.html 8.72 KB
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rule.html 8.72 KB
Part 21-Module 01-Lesson 05_Scripting/11. Errors and Exceptions.html 8.72 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps.html 8.72 KB
Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example-LCZG4wlEFXE.zh-CN.vtt 8.72 KB
Part 06-Module 01-Lesson 03_Analyzing Data/11. Unwind Operator-6wBjB3Ca5H4.en.vtt 8.72 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data.html 8.71 KB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart.html 8.71 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Video Other Sampling Distributions.html 8.71 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size.html 8.71 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular.html 8.71 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information.html 8.71 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference.html 8.71 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Video JOINing Subqueries.html 8.71 KB
Part 21-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.ar.vtt 8.71 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem.html 8.71 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2-1JRk6dgQhkE.ar.vtt 8.71 KB
Part 11-Module 01-Lesson 03_SVM/27. SVM Mini-Project.html 8.71 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic.html 8.71 KB
Part 14-Module 01-Lesson 05_Analyzing Results/09. Single Metric Example--QwMdwqUq9c.ar.vtt 8.7 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom.html 8.7 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles.html 8.7 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/19. Query the Dataset 2.html 8.69 KB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary.html 8.69 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size.html 8.69 KB
Part 11-Module 01-Lesson 12_Feature Selection/24. Overfitting a Decision Tree 2.html 8.69 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/Project Rubric - Technical Interview Practice.html 8.68 KB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression.html 8.68 KB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart.html 8.68 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Video Introduction to Notation.html 8.68 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs.html 8.68 KB
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4.html 8.68 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training.html 8.67 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science.html 8.67 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference.html 8.67 KB
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2.html 8.67 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test.html 8.67 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples.html 8.67 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/08. NumPy Matrix Multiplication.html 8.67 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.en.vtt 8.66 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs.html 8.66 KB
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails.html 8.66 KB
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation.html 8.66 KB
Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier.html 8.65 KB
Part 17-Module 01-Lesson 16_Logistic Regression/33. Video Congratulations.html 8.65 KB
Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/13. Carat Frequency Polygon.html 8.65 KB
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple.html 8.65 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin.html 8.65 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/08. Defining Metrics Other Techniques.html 8.65 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD.html 8.65 KB
Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR.html 8.64 KB
Part 11-Module 01-Lesson 12_Feature Selection/26. Accuracy of Your Overfit Decision Tree.html 8.64 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies.html 8.64 KB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1.html 8.64 KB
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3.html 8.64 KB
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4.html 8.64 KB
Part 11-Module 01-Lesson 14_Validation/17. Your First (Overfit) POI Identifier.html 8.64 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/16. Sean's NFL Fan Sentiment Study.html 8.63 KB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key.html 8.63 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview.html 8.63 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/09. Quiz Self JOINs.html 8.63 KB
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS.html 8.63 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics.html 8.62 KB
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8.html 8.62 KB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/07. Stories.html 8.62 KB
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7.html 8.62 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/27. Communicating Results Practice.html 8.62 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/28. Dict-to-array conversion.html 8.62 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API.html 8.62 KB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad.html 8.62 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/17. Exploring Student Engagement-6QLiscx_zIY.ar.vtt 8.61 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs.html 8.61 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/30. Missing POIs 2 (optional).html 8.61 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness.html 8.61 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/05. Quiz Window Functions 2.html 8.61 KB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD.html 8.61 KB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans.html 8.61 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.zh-CN.vtt 8.61 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/26. Unfilled Features.html 8.6 KB
Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next.html 8.6 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic.html 8.6 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2.html 8.6 KB
Part 11-Module 01-Lesson 13_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.ar.vtt 8.59 KB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1.html 8.59 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process.html 8.58 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/04. Data Types.html 8.58 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/06. Solutions Window Functions 2.html 8.58 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video.html 8.58 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. SQL Subquery Video-10pmKmTI_CA.pt-BR.vtt 8.58 KB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots.html 8.58 KB
Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators-cleAY1-Jboc.ar.vtt 8.57 KB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features.html 8.57 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4.html 8.57 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/03. Accuracy vs. Training Set Size.html 8.56 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/29. Lessons Learned-_dnp6ItYOdA.pt-BR.vtt 8.56 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/img/explore.png 8.56 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Video Dummy Variables Recap.html 8.56 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.pt-BR.vtt 8.56 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/06. Text General Notes for Building Data Dashboards with Trina.html 8.56 KB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency.html 8.56 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD.html 8.55 KB
Part 21-Module 01-Lesson 05_Scripting/07. Editing a Python Script.html 8.55 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/13. 30. Teaching Method.html 8.55 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/14. 31. Reading Scores.html 8.55 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two.html 8.55 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/14. Features in the Enron Dataset.html 8.55 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/27. Text Recap.html 8.55 KB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT.html 8.55 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion.html 8.55 KB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video.html 8.55 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM.html 8.54 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. Video JOINs with Comparison Operators.html 8.54 KB
Part 16-Module 03-Lesson 02_SQL Joins/07. Text Primary and Foreign Keys.html 8.54 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3.html 8.54 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/02. Text Optional Lessons Note.html 8.53 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/13. Gather (Summary).html 8.53 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d.html 8.53 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/24. Enron CFO.html 8.53 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/01. Introduction.html 8.53 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/03. Metric Definition Overview, Part 2-0DyLzS2ux7g.ar.vtt 8.53 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/09. 12. Define Operational Definition.html 8.53 KB
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters.html 8.53 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory.html 8.53 KB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations.html 8.53 KB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing.html 8.52 KB
Part 11-Module 01-Lesson 09_Clustering/21. Clustering with 3 Features.html 8.52 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post.html 8.52 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/22. Enron CEO.html 8.52 KB
Part 21-Module 01-Lesson 05_Scripting/16. Accessing Error Messages.html 8.51 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/25. Dot Notation-OcPW6xp8DfE.ar.vtt 8.51 KB
Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analyses.html 8.51 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics.html 8.51 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Write the Introduction.html 8.51 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/32. Survey Says!.html 8.5 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail.html 8.5 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post.html 8.5 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/23. Enron Chairman.html 8.5 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/16. 22. Convenience Samples.html 8.5 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/24. Clean (Summary).html 8.5 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/10. 13. Research Studies.html 8.49 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/08. price vs. carat.html 8.49 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory.html 8.49 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines.html 8.49 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs.html 8.49 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2.html 8.49 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory.html 8.49 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/img/share.png 8.48 KB
Part 17-Module 01-Lesson 14_Regression/10. Video What Defines A Line.html 8.48 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/02. Self-Practice Behavioral Questions.html 8.48 KB
Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/01. Diamonds.html 8.48 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/26. Adding and Formatting China's Red Dot.html 8.48 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/11. 14. Variables.html 8.48 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2.html 8.48 KB
Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables.html 8.48 KB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information.html 8.47 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum.html 8.47 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB.html 8.47 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/22. 38. Insomnia.html 8.47 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/11. D3 Chain Syntax and Changing the Navbar.html 8.47 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size.html 8.47 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data.html 8.47 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format.html 8.47 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data.html 8.47 KB
Part 21-Module 01-Lesson 03_Control Flow/34. Conclusion.html 8.46 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution.html 8.46 KB
Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files on Hand.html 8.46 KB
Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI.html 8.46 KB
Part 11-Module 01-Lesson 08_Outliers/12. Slope After Cleaning.html 8.45 KB
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!.html 8.45 KB
Part 21-Module 01-Lesson 05_Scripting/01. Introduction.html 8.45 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/08. Top City Favorite Music.html 8.44 KB
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!.html 8.44 KB
Part 17-Module 01-Lesson 14_Regression/02. Video Introduction to Machine Learning.html 8.44 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess.html 8.44 KB
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size.html 8.44 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation.html 8.44 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2.html 8.43 KB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3.html 8.43 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots.html 8.43 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI.html 8.43 KB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection.html 8.43 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/03. Valid MongoDB Documents.html 8.43 KB
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories.html 8.43 KB
Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics.html 8.43 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/18. Visual Encodings.html 8.43 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working in the Javascript Console.html 8.43 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles.html 8.43 KB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition).html 8.43 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Video Introduction to Aggregation.html 8.43 KB
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric.html 8.43 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/03. Quiz Window Functions 1.html 8.42 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula.html 8.42 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems.html 8.42 KB
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics.html 8.42 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3.html 8.42 KB
Part 04-Module 01-Lesson 01_Anaconda/04. Managing packages.html 8.42 KB
Part 16-Module 01-Lesson 01_Anaconda/04. Managing packages.html 8.42 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. Video COUNT NULLs.html 8.42 KB
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About with More Than Two Variables.html 8.42 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below.html 8.42 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations.html 8.42 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro.html 8.42 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/12. Dual Axis.html 8.42 KB
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4.html 8.41 KB
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5.html 8.41 KB
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6.html 8.41 KB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature.html 8.41 KB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/06. Formatting.html 8.41 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2.html 8.41 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/07. 20. Which Are True.html 8.41 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/08. Document Selectors and Queries.html 8.41 KB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye.html 8.41 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot.html 8.4 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data.html 8.4 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Video HAVING.html 8.4 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/18. Solutions Comparing a Row to Previous Row.html 8.4 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs.html 8.4 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/07. Supported Data Models.html 8.4 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/04. Solutions LEFT RIGHT.html 8.4 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections.html 8.4 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/08. Quiz ROW_NUMBER RANK.html 8.4 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place.html 8.4 KB
Part 05-Module 01-Lesson 05_Data Quality/08. Example Using our Blueprint.html 8.4 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/10. Inter- vs. Intra-User Experiments.html 8.4 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed.html 8.4 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson....html 8.4 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/29. 50. Depression.html 8.39 KB
Part 17-Module 01-Lesson 14_Regression/16. Video How to Interpret the Results.html 8.39 KB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression.html 8.39 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative.html 8.39 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console.html 8.39 KB
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1.html 8.39 KB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators.html 8.39 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/19. Sensitivity and Robustness Example.html 8.39 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. Video Welcome!.html 8.38 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test.html 8.38 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms.html 8.38 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE.html 8.38 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Loading D3.html 8.38 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test.html 8.38 KB
Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization.html 8.37 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/12. Metric Definition and Data Capture.html 8.37 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/12. Internal Process.html 8.37 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar.html 8.37 KB
Part 18-Module 02-Lesson 01_Gathering Data/24. Other File Formats.html 8.37 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet.html 8.37 KB
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion.html 8.37 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/15. JSON Playground-la_rboWWjQI.zh-CN.vtt 8.37 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/05. 15. Variable Relationships.html 8.37 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3.html 8.36 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account.html 8.36 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys.html 8.36 KB
Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty.html 8.36 KB
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Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables.html 8.36 KB
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Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical of Outliers and Anomalies.html 8.36 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account.html 8.36 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API.html 8.36 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Video Introduction to Summary Statistics.html 8.36 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing.html 8.35 KB
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/12. 29. Extreme Temperature.html 8.35 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes.html 8.35 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution.html 8.35 KB
Part 12-Module 02-Lesson 02_List-Based Collections/04. Python Lists.html 8.35 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations.html 8.35 KB
Part 17-Module 01-Lesson 14_Regression/17. Video Does the Line Fit the Data Well.html 8.35 KB
Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/06. Price by Cut Histograms.html 8.34 KB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data.html 8.34 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes.html 8.34 KB
Part 18-Module 02-Lesson 01_Gathering Data/img/client-server.png 8.34 KB
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Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions.html 8.34 KB
Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.ar.vtt 8.33 KB
Part 12-Module 02-Lesson 06_Graphs/05. Graph Practice.html 8.33 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements.html 8.33 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. ScreenCast Difference In Means.html 8.33 KB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation.html 8.33 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/07. Show me.html 8.33 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution.html 8.33 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel.html 8.33 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/29. Survey Says!.html 8.33 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3.html 8.33 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.ar.vtt 8.33 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB.html 8.32 KB
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width.html 8.32 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/04. NumPy Arrays-UG924zKZF7U.ar.vtt 8.32 KB
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro.html 8.32 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater.html 8.32 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/04. Countries with most Invoices.html 8.32 KB
Part 11-Module 01-Lesson 11_Text Learning/19. Clean Away Signature Words.html 8.32 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score.html 8.32 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/01. price vs. x.html 8.31 KB
Part 15-Module 01-Lesson 02_Design Principles/10. Pre-Attentive Processing.html 8.31 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3.html 8.31 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview.html 8.31 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness.html 8.31 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/03. Quiz LEFT RIGHT.html 8.31 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/06. 19. n.html 8.31 KB
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Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library.html 8.3 KB
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Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3.html 8.3 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses.html 8.3 KB
Part 21-Module 01-Lesson 04_Functions/11. Lambda Expressions.html 8.3 KB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview.html 8.3 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/09. Other Techniques, Part 2.html 8.3 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/14. Filtering and Segmenting.html 8.3 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review.html 8.29 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/02. Video Introduction to NULLs.html 8.29 KB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords.html 8.29 KB
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/30. Lessons Learned, Part 2.html 8.29 KB
Part 16-Module 03-Lesson 02_SQL Joins/15. Text Other JOIN Notes.html 8.29 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory.html 8.29 KB
Part 18-Module 03-Lesson 01_Assessing Data/19. How Data Gets Dirty and Messy.html 8.28 KB
Part 11-Module 01-Lesson 09_Clustering/19. Clustering Features.html 8.28 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory.html 8.28 KB
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/12. Solutions Aggregates in Window Functions.html 8.28 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity.html 8.27 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge.html 8.27 KB
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability.html 8.27 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts.html 8.27 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales.html 8.26 KB
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction.html 8.26 KB
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Part 16-Module 02-Lesson 01_The Data Analysis Process/14. Assessing and Building Intuition.html 8.26 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/20. Recap.html 8.26 KB
Part 18-Module 02-Lesson 01_Gathering Data/03. Dataset Finding the Best Movies.html 8.25 KB
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Part 17-Module 01-Lesson 11_Confidence Intervals/12. Video Other Language Associated with Confidence Intervals.html 8.25 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error.html 8.25 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations.html 8.25 KB
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Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example.html 8.25 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/08. Intro to PyMongo.html 8.25 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/04. price vs. depth.html 8.25 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication.html 8.24 KB
Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/11. Interquartile Range - IQR.html 8.24 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution.html 8.24 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion.html 8.24 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/23. The Facebook Offering.html 8.24 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/16. Gapminder Revisited.html 8.24 KB
Part 16-Module 03-Lesson 02_SQL Joins/05. Solution Your First JOIN.html 8.24 KB
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Part 09-Module 01-Lesson 05_Explore Two Variables/25. Smoothing Conditional Means.html 8.24 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment.html 8.23 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited.html 8.23 KB
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Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Video Data Types Summary.html 8.23 KB
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Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/09. Solutions ROW_NUMBER RANK.html 8.23 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/20. 36. Student Satisfaction.html 8.23 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. Video What is Data Why is it important.html 8.23 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance.html 8.2 KB
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/10. Intro to XLRD.html 8.2 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax.html 8.2 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/13. Reading CSV Files.html 8.2 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/18. Cleaning Practice.html 8.2 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape.html 8.2 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data.html 8.19 KB
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Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator.html 8.17 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/20. Practice Viz Top Skills.html 8.17 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Video From Sampling Distributions to Confidence Intervals.html 8.17 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-xOSypbjALh4.en.vtt 8.17 KB
assets/css/fonts/KaTeX_Size3-Regular.ttf 8.16 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations.html 8.16 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/01. 4. Characteristic of a Sample.html 8.16 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/20. 41. Placebo Control Condition.html 8.16 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Screencast Fitting A Multiple Linear Regression Model.html 8.16 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources-OYl-saB2vWE.en.vtt 8.16 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity.html 8.15 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/16. Summary Metrics-ghMD3AfjLZc.ar.vtt 8.14 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/09. Statistical vs. Practical Significance.html 8.14 KB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants.html 8.14 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/22. 43. Measuring Constructs.html 8.14 KB
Part 05-Module 01-Lesson 05_Data Quality/03. Problematic Parts.html 8.14 KB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency.html 8.14 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data.html 8.14 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/13. Conclusions Visuals.html 8.14 KB
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight.html 8.14 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris.html 8.13 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/11. Gapminder Multivariate Analysis.html 8.13 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/04. Solutions Write Your First Subquery.html 8.13 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/14. Video Correct Interpretations of Confidence Intervals.html 8.13 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/19. 40. Random Assignment.html 8.13 KB
Part 11-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn.html 8.13 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4.html 8.13 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/10. Intro to XLRD-TcWtpvLSoG0.zh-CN.vtt 8.13 KB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/20. 34. Table vs. Histogram.html 8.13 KB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/03. 9. Common Decade.html 8.13 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport.html 8.13 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.en-US.vtt 8.13 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/21. 42. Why Placebo.html 8.12 KB
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Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/25. 46. Blind Studies.html 8.12 KB
Part 14-Module 01-Lesson 06_Final Project/05. Calculating Number of Pageviews.html 8.12 KB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/16. 30. X-Axis Represent!.html 8.12 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/23. 44. Participants.html 8.12 KB
Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme.html 8.12 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/02. 5. Freshman 15.html 8.12 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/26. 47. Causality.html 8.12 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example.html 8.12 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols.html 8.11 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization.html 8.11 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Video Statistical vs. Practical Significance.html 8.11 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/03. 8. SAT Scores.html 8.11 KB
Part 18-Module 04-Lesson 01_Cleaning Data/02. Lesson Outline.html 8.11 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/17. 35. Landmines.html 8.11 KB
Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error.html 8.11 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/10. Solutions CONCAT.html 8.11 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question.html 8.11 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps.html 8.1 KB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings.html 8.1 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Screencast How to Add Higher Order Terms.html 8.1 KB
Part 11-Module 01-Lesson 14_Validation/13. GridSearchCV in sklearn.html 8.09 KB
Part 14-Module 01-Lesson 06_Final Project/04. Calculating Standard Deviation.html 8.09 KB
Part 19-Module 01-Lesson 02_Design/19. Same Data, Different Stories.html 8.09 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/img/data-analysis-process.png 8.09 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores.html 8.09 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors.html 8.09 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Video WITH.html 8.09 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores.html 8.09 KB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer.html 8.08 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off.html 8.08 KB
Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song.html 8.08 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables.html 8.08 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/05. Proportion of Friendships Initiated.html 8.08 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/04. Solutions FULL OUTER JOIN.html 8.08 KB
Part 16-Module 03-Lesson 02_SQL Joins/13. Video Motivation for Other JOINs.html 8.08 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk.html 8.08 KB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/02. Question 2.html 8.07 KB
Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2.html 8.07 KB
Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.ar.vtt 8.07 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/18. Matplotlib Example.html 8.07 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources-OYl-saB2vWE.pt-BR.vtt 8.07 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Video Higher Order Terms.html 8.07 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs.html 8.07 KB
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution.html 8.07 KB
Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.ar.vtt 8.07 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course.html 8.07 KB
Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page.html 8.07 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs.html 8.06 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing.html 8.06 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/05. DAP Overview-qdV4sifMmWI.en.vtt 8.06 KB
Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z.html 8.06 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs.html 8.06 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples.html 8.06 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error.html 8.06 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy.html 8.06 KB
Part 21-Module 01-Lesson 05_Scripting/23. Solution The Standard Library.html 8.06 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.ar.vtt 8.06 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.ar.vtt 8.06 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/03. Binary Search Practice.html 8.06 KB
Part 04-Module 03-Lesson 01_Investigate a Dataset/Project Description - Investigate a Dataset.html 8.05 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/12. Mystery Code.html 8.05 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals.html 8.05 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions.html 8.05 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots.html 8.05 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias.html 8.05 KB
Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.en-US.vtt 8.05 KB
Part 11-Module 01-Lesson 09_Clustering/23. Salary Range.html 8.05 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Screencast Dummy Variables.html 8.04 KB
Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.en.vtt 8.04 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I.html 8.04 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Video Aliases for Multiple Window Functions.html 8.04 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model.html 8.04 KB
Part 12-Module 01-Lesson 05_Interview Practice/08. Keep Practicing!.html 8.04 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Video Interpreting Interactions.html 8.03 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.pt-BR.vtt 8.03 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data.html 8.03 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center.html 8.03 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/Project Description - Technical Interview Practice.html 8.03 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/06. Cleaning Column Labels.html 8.03 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16.html 8.03 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/20. 20. Which Distribution.html 8.03 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques.html 8.02 KB
Part 10-Module 01-Lesson 03_Udacity Professional Profile/07. Projects.html 8.02 KB
Part 13-Module 01-Lesson 04_Design Principles/index.html 8.02 KB
Part 17-Module 01-Lesson 14_Regression/04. Video Introduction to Linear Regression.html 8.02 KB
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database.html 8.01 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/18. Sensitivity and Robustness-T2QI3p0yDNk.ar.vtt 8.01 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. ScreenCast Sampling Distributions and Confidence Intervals.html 8.01 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes.html 8.01 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema.html 8.01 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-FC_GNjqj5zI.en.vtt 8.01 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds.html 8.01 KB
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron.html 8 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2.html 8 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting with Appending.html 8 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1.html 8 KB
Part 07-Module 01-Lesson 01_GitHub Review/17. Resources in Your Career Portal.html 8 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice.html 8 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above.html 8 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods.html 8 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion-im8-LLU5J_Y.ar.vtt 7.99 KB
Part 21-Module 01-Lesson 05_Scripting/15. Solution Handling Input Errors.html 7.99 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/16. Results with Merged Dataset.html 7.99 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations.html 7.99 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-W4Xno_vJvZM.pt-BR.vtt 7.99 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition.html 7.99 KB
Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1.html 7.99 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Video Potential Problems.html 7.99 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. ScreenCast Traditional Confidence Interval Methods.html 7.99 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition.html 7.98 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You.html 7.98 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion.html 7.98 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.ar.vtt 7.98 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion.html 7.97 KB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary.html 7.97 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20.html 7.97 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/07. Solutions JOINs with Comparison Operators.html 7.97 KB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings.html 7.97 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process.html 7.97 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data.html 7.96 KB
Part 11-Module 01-Lesson 10_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.ar.vtt 7.96 KB
Part 06-Module 01-Lesson 03_Analyzing Data/03. Example of Aggregation Framework-pOJAW4jTjr0.en.vtt 7.96 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5.html 7.96 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!.html 7.96 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation.html 7.96 KB
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion.html 7.96 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/16. 16. Population Distribution Shape.html 7.95 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution.html 7.95 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.en.vtt 7.95 KB
Part 17-Module 01-Lesson 14_Regression/15. Screencast Fitting A Regression Line in Python.html 7.95 KB
Part 09-Module 01-Lesson 04_Problem Set Explore One Variable/02. Price Histogram.html 7.94 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts.html 7.94 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/03. Intro to AB Testing-ASQubLvGuxY.pt-BR.vtt 7.94 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads.html 7.93 KB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations.html 7.93 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!.html 7.93 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's.html 7.92 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/09. The Facebook Offering.html 7.92 KB
Part 18-Module 02-Lesson 01_Gathering Data/19. Mashup Solution.html 7.92 KB
Part 17-Module 01-Lesson 14_Regression/22. Text Recap + Next Steps.html 7.92 KB
Part 17-Module 01-Lesson 04_Probability/20. Text Recap + Next Steps.html 7.92 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's.html 7.92 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/24. 45. What Proportion.html 7.92 KB
Part 11-Module 01-Lesson 11_Text Learning/17. Warming Up with parseOutText().html 7.92 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads.html 7.92 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads.html 7.91 KB
Part 14-Module 01-Lesson 05_Analyzing Results/15. Multiple Metrics Example 3.html 7.91 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/15. 15. Probability Decreased.html 7.91 KB
Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/05. 8. True or False.html 7.91 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.pt-BR.vtt 7.91 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2.html 7.91 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3.html 7.91 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Video POSITION, STRPOS, SUBSTR.html 7.91 KB
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris.html 7.9 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head.html 7.9 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5.html 7.9 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/10. Solutions Self JOINs.html 7.9 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Video Recap.html 7.9 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness.html 7.89 KB
Part 05-Module 01-Lesson 05_Data Quality/14. Auditing Accuracy 2-5xY3sCBHkOk.ar.vtt 7.89 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness.html 7.89 KB
Part 17-Module 01-Lesson 14_Regression/13. Video Fitting A Regression Line.html 7.89 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/14. 18. Symbols = Fun Fun Fun!.html 7.89 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/Project Description - Craft Your Cover Letter.html 7.88 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2.html 7.88 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula.html 7.88 KB
Part 21-Module 01-Lesson 04_Functions/04. Solution Defining Functions.html 7.88 KB
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Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/01. SQL Scramble Top 10 Composers.html 7.87 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements.html 7.87 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/20. Type Quality Plot with Matplotlib.html 7.86 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. Video + Text What's Ahead.html 7.86 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/07. 9. Survey to Friends.html 7.86 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings.html 7.85 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example.html 7.85 KB
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2.html 7.85 KB
Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2.html 7.85 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Video More On Subqueries.html 7.85 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Handoff to Juno Lee.html 7.85 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/13. Solutions UNION.html 7.85 KB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables.html 7.85 KB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness.html 7.85 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails.html 7.85 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data.html 7.85 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-22sQCo6ovH0.ar.vtt 7.84 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data.html 7.84 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4.html 7.84 KB
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate.html 7.84 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous.html 7.84 KB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-v4UGBUB6jO4.ar.vtt 7.84 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data with Visuals.html 7.84 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example.html 7.84 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends.html 7.84 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5.html 7.83 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6.html 7.83 KB
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes.html 7.83 KB
Part 10-Module 01-Lesson 03_Udacity Professional Profile/04. Top Section.html 7.83 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3.html 7.83 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4.html 7.83 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-WmJKPUthUPw.ar.vtt 7.83 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-WmJKPUthUPw.ar.vtt 7.83 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/05. Your Udacity Professional Profile.html 7.82 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios.html 7.82 KB
Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.ar.vtt 7.82 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/07. Promotional Music Event.html 7.82 KB
Part 11-Module 01-Lesson 08_Outliers/14. Enron Outliers.html 7.81 KB
Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First.html 7.81 KB
Part 11-Module 01-Lesson 08_Outliers/10. Slope of Regression with Outliers.html 7.8 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/10. Heading to France.html 7.8 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/49. The Future of Data Visualizations--CWbVBYBYWU.en.vtt 7.8 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial.html 7.8 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling and EDA.html 7.8 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Video Confidence Interval Applications.html 7.8 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/06. 6. Udacians' Facebook Friends (mean +- std dev).html 7.8 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation.html 7.8 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two.html 7.8 KB
Part 16-Module 03-Lesson 02_SQL Joins/18. Video JOINs and Filtering.html 7.8 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities.html 7.79 KB
Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes-vL9FcO_9dCA.pt-BR.vtt 7.79 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results.html 7.79 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables.html 7.79 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/11. Time for Live Practice with Pramp.html 7.79 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/10. Creating a slideshow.html 7.79 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/10. Creating a slideshow.html 7.79 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability.html 7.79 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting with Pandas.html 7.78 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/08. Click Through Rate.html 7.78 KB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction.html 7.78 KB
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Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions.html 7.78 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/08. Solutions More On Subqueries.html 7.77 KB
Part 05-Module 01-Lesson 05_Data Quality/18. Auditing Uniformity-cF0AEW4SIUM.pt-BR.vtt 7.76 KB
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/07. Resume Review (Prior Industry Experience).html 7.76 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/17. Text Recap + Next Steps.html 7.76 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. David's Data Wrangling Example-TN-CWy3GK44.pt-BR.vtt 7.76 KB
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/09. Fixing Data Types Pt 1.html 7.75 KB
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/14. 28. Thinking About Distributions.html 7.73 KB
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Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data.html 7.73 KB
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!.html 7.72 KB
Part 11-Module 01-Lesson 11_Text Learning/18. Deploying Stemming.html 7.72 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction.html 7.72 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226.html 7.72 KB
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/17. Question 5.html 7.71 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/07. 7. Udacians' Facebook Friends (proportion).html 7.71 KB
Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/12. Mystery Code.html 7.71 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/15. 32. Which Is Better.html 7.71 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/index.html 7.71 KB
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Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.en.vtt 7.71 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection.html 7.71 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion.html 7.71 KB
Part 13-Module 02-Lesson 01_Make Effective Data Visualization/Project Description - Make Effective Data Visualization.html 7.7 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview.html 7.7 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars.html 7.7 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion.html 7.69 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/13. Solutions CAST.html 7.69 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Video Introduction to Window Functions.html 7.69 KB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips.html 7.69 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/05. 6. Characteristic of a Population.html 7.69 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/27. 48. Depression.html 7.69 KB
Part 16-Module 03-Lesson 02_SQL Joins/03. Video Introduction to JOINs.html 7.69 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/06. 7. Sample Approximates Population.html 7.69 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value.html 7.69 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262.html 7.68 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value.html 7.68 KB
Part 17-Module 01-Lesson 14_Regression/01. Video Introduction.html 7.68 KB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac.html 7.68 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion.html 7.68 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Video Aggregates in Window Functions.html 7.68 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/19. 33. All Kinds of Variables.html 7.68 KB
Part 03-Module 01-Lesson 14_PS 5a Standardizing/14. 19. True or False.html 7.68 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/07. Resume Review (Career Change).html 7.68 KB
Part 11-Module 01-Lesson 14_Validation/18. Deploying a TrainingTesting Regime.html 7.67 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview.html 7.67 KB
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Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/03. 2. Sleepy College Students.html 7.67 KB
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Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB.html 7.67 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests.html 7.66 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/06. Quiz POSITION, STRPOS, SUBSTR - AME DATA AS QUIZ 1.html 7.66 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/02. 1. All California Residents.html 7.66 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/18. 18. Mean of Sampling Distribution.html 7.66 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion.html 7.66 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/04. 3. Not Enough Sleep....html 7.66 KB
Part 19-Module 01-Lesson 02_Design/21. Recap.html 7.66 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB.html 7.66 KB
Part 11-Module 01-Lesson 07_Regressions/index.html 7.66 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Video Introduction to Percentiles.html 7.65 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather (CSV Files).html 7.65 KB
Part 12-Module 02-Lesson 02_List-Based Collections/12. Queue Practice.html 7.65 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries.html 7.64 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/19. 19. SD of Sampling Distribution.html 7.64 KB
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages.html 7.64 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/06. prop_initiated vs. tenure.html 7.64 KB
Part 11-Module 01-Lesson 08_Outliers/17. Any More Outliers.html 7.64 KB
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data.html 7.63 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes.html 7.63 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/01. 1. Central Limit Theorem.html 7.62 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Video ROW_NUMBER RANK.html 7.62 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather (Intro).html 7.62 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/03. 3. Average Difference.html 7.62 KB
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/01. 1. True or False.html 7.62 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures.html 7.62 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/07. Resume Review (Entry-level).html 7.62 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size.html 7.62 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree.html 7.61 KB
Part 11-Module 01-Lesson 10_Feature Scaling/17. When to Deploy Feature Scaling.html 7.61 KB
Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate.html 7.61 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/14. 14. Probability.html 7.61 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries.html 7.61 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents.html 7.61 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Video Recap.html 7.61 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/14. Population vs. Cohort Example.html 7.61 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example.html 7.61 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/05. 5. Standard Error.html 7.61 KB
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Part 11-Module 01-Lesson 11_Text Learning/20. TfIdf It.html 7.6 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication.html 7.6 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size.html 7.6 KB
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots.html 7.59 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/14. Types of Merges.html 7.59 KB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction.html 7.59 KB
Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/11. 22. Cell Phone Law Decision.html 7.59 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/09. Solution Video More On Subqueries.html 7.59 KB
Part 18-Module 03-Lesson 01_Assessing Data/21. Assessing Summary.html 7.59 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance.html 7.58 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests.html 7.58 KB
Part 12-Module 02-Lesson 05_Trees/04. Tree Practice.html 7.58 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/17. More Work Than We Thought.html 7.58 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Video LEFT RIGHT.html 7.58 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions.html 7.57 KB
Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion.html 7.57 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries.html 7.57 KB
Part 21-Module 01-Lesson 04_Functions/09. Quiz Documentation.html 7.57 KB
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Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual.html 7.57 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator.html 7.56 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update.html 7.56 KB
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Part 16-Module 01-Lesson 01_Anaconda/03. Installing Anaconda.html 7.56 KB
Part 03-Module 01-Lesson 14_PS 5a Standardizing/07. 10. Scores.html 7.56 KB
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Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator.html 7.56 KB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/11. 24. Analyze Histogram.html 7.55 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats.html 7.55 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2.html 7.55 KB
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Part 02-Module 02-Lesson 01_Project Prep/Project Rubric - P0 Analyze Chopstick Length (Optional).html 7.55 KB
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Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators.html 7.54 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/27. Set Unset.html 7.54 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation.html 7.54 KB
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240.html 7.54 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results.html 7.54 KB
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Part 05-Module 02-Lesson 02_Problem Set Data and Tables/12. Mystery Code.html 7.53 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering.html 7.52 KB
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Part 03-Module 01-Lesson 12_PS 4 Variability/10. 10. Where's Your Score (sd = 5).html 7.51 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/12. 12. Where's Your Score (sd = 10).html 7.51 KB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/03. Question 3.html 7.51 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d.html 7.51 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview.html 7.5 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion.html 7.5 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/09. Getting Musicians.html 7.5 KB
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion.html 7.5 KB
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/07. Appending Data.html 7.5 KB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/07. 18. Calculate Bin Size.html 7.49 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses.html 7.49 KB
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Part 11-Module 01-Lesson 09_Clustering/18. K-Means Clustering Mini-Project.html 7.48 KB
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset.html 7.47 KB
Part 15-Module 01-Lesson 02_Design Principles/06. Common and Less Common Plots in Plot.ly.html 7.47 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion.html 7.46 KB
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Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/02. 2. Rare Blood.html 7.45 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/14. 14. BBC Sample Scores (Variability).html 7.45 KB
Part 19-Module 01-Lesson 02_Design/13. Using Color.html 7.45 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles.html 7.44 KB
Part 14-Module 01-Lesson 06_Final Project/03. Choosing Evaluation Metrics.html 7.44 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate.html 7.44 KB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction.html 7.44 KB
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Video Subquery Conclusion.html 7.44 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/11. Spectrum of Data Viz Tools.html 7.44 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu.html 7.43 KB
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Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/02. 2. Location of Sample Mean.html 7.42 KB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3.html 7.42 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components.html 7.42 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data.html 7.42 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/20. Three-Dimensional Data.html 7.42 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/20. Three-Dimensional Data.html 7.42 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/04. Price vs. Volume and Diamond Clarity.html 7.41 KB
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Part 11-Module 01-Lesson 08_Outliers/16. Remove Enron Outlier.html 7.41 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/index.html 7.41 KB
Part 18-Module 03-Lesson 01_Assessing Data/22. Conclusion.html 7.4 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/13. Resources in Your Career Portal.html 7.4 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example.html 7.39 KB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color.html 7.39 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/07. Solutions POSITION, STRPOS, SUBSTR.html 7.39 KB
Part 04-Module 03-Lesson 01_Investigate a Dataset/01. Project Overview.html 7.39 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview.html 7.39 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML.html 7.38 KB
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Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects.html 7.38 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/02. Linear Regression Models.html 7.38 KB
Part 14-Module 02-Lesson 01_Design an AB Test/Project Description - Design an AB Test.html 7.37 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/08. 8. Udacians' Facebook Friends (sample sd).html 7.37 KB
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Part 14-Module 01-Lesson 06_Final Project/02. Choosing Invariant Metrics.html 7.36 KB
Part 02-Module 02-Lesson 01_Project Prep/01. Project Overview.html 7.36 KB
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Part 03-Module 01-Lesson 12_PS 4 Variability/01. 1. Udacians' Facebook Friends (Mean).html 7.36 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II.html 7.36 KB
Part 11-Module 01-Lesson 04_Decision Trees/index.html 7.36 KB
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means.html 7.36 KB
Part 19-Module 01-Lesson 02_Design/08. Data Ink Ratio.html 7.35 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/19. Question 7.html 7.35 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/01. Price Histograms with Facet and Color.html 7.35 KB
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Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/20. Question 8.html 7.34 KB
Part 03-Module 02-Lesson 01_Test a Perceptual Phenomenon/Project Rubric - Test a Perceptual Phenomenon.html 7.34 KB
Part 21-Module 01-Lesson 04_Functions/10. Solution Documentation.html 7.34 KB
Part 03-Module 01-Lesson 09_PS 3a Central Tendency/07. 7. Positively Skewed.html 7.34 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/23. Learning Effects-nFpIDWPUDm8.en.vtt 7.34 KB
Part 21-Module 01-Lesson 04_Functions/18. Conclusion.html 7.34 KB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction.html 7.33 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/02. 2. Udacians' Facebook Friends (Avg. Dev).html 7.33 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/04. 4. Udacians' Facebook Friends (Variance).html 7.33 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/05. 5. Udacians' Facebook Friends (Std Dev).html 7.33 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.pt-BR.vtt 7.32 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots.html 7.32 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/07. Parsing XML.html 7.32 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/14. Question 2.html 7.32 KB
Part 17-Module 01-Lesson 14_Regression/21. Video Recap.html 7.32 KB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning.html 7.32 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview.html 7.32 KB
Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/07. DB API - Playground.html 7.31 KB
Part 11-Module 01-Lesson 08_Outliers/15. Identify the Biggest Enron Outlier.html 7.31 KB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.ar.vtt 7.31 KB
Part 03-Module 01-Lesson 12_PS 4 Variability/03. 3. Udacians' Facebook Friends (SS).html 7.31 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data.html 7.31 KB
Part 11-Module 02-Lesson 01_Identify Fraud from Enron Email/01. Project Overview.html 7.3 KB
Part 11-Module 01-Lesson 11_Text Learning/06. Bag of Words in Sklearn.html 7.3 KB
Part 11-Module 01-Lesson 11_Text Learning/21. Accessing TfIdf Features.html 7.3 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type Quality Plot - Part 1.html 7.3 KB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items.html 7.3 KB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/10. Question 10.html 7.29 KB
Part 21-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.pt-BR.vtt 7.29 KB
Part 06-Module 01-Lesson 03_Analyzing Data/17. Indexes-tSgPhxZdhLk.pt-BR.vtt 7.29 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/06. Next Two Principles.html 7.29 KB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies.html 7.29 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/16. Video Confidence Intervals Hypothesis Tests.html 7.29 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/index.html 7.29 KB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction.html 7.29 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/14. Pandas Query.html 7.29 KB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter.html 7.28 KB
Part 11-Module 01-Lesson 02_Naive Bayes/index.html 7.28 KB
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie.html 7.28 KB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty vs. Messy 1.html 7.28 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score.html 7.28 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/10. PriceCarat Binned, Faceted, Colored.html 7.28 KB
Part 15-Module 01-Lesson 02_Design Principles/12. Careful with Color.html 7.28 KB
Part 16-Module 03-Lesson 01_Basic SQL/index.html 7.27 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small.html 7.27 KB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/07. 17. Deal or No Deal (Frequency).html 7.27 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/07. Coding-zhQYREUI8Z0.pt-BR.vtt 7.27 KB
Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/15. 15. Meanings.html 7.27 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details.html 7.27 KB
Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.pt-BR.vtt 7.27 KB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/08. 21. Commute Time.html 7.26 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-z1UX9i9_piQ.zh-CN.vtt 7.26 KB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story.html 7.26 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-HGYW-skXvY4.ar.vtt 7.26 KB
Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.en.vtt 7.26 KB
Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.en.vtt 7.26 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/12. Intro to JSON-Fi7RjhBLobY.ar.vtt 7.26 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Video Self JOINs.html 7.25 KB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/15. A Tale of Four Quadrants.html 7.25 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/05. Lets Make a Map-mOZuq2JoN-k.ar.vtt 7.25 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/01. About This Lesson.html 7.25 KB
Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video.html 7.25 KB
Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table.html 7.25 KB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion.html 7.24 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/17. Cleaning Example-7bnSPYtPDzQ.en.vtt 7.24 KB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/02. 8. Calculate Percentages.html 7.23 KB
Part 03-Module 01-Lesson 29_PS 10b t-Tests, Part 2/13. 24. Cell Phone Law CI.html 7.23 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping.html 7.23 KB
Part 21-Module 01-Lesson 04_Functions/01. Introduction.html 7.23 KB
Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/01. 3. t-Test.html 7.23 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/01. Problem Set Numbering.html 7.23 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma.html 7.23 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Video Communicating With Your Data.html 7.23 KB
Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/03. WARM UP - JOIN to Subquery.html 7.22 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview.html 7.22 KB
Part 11-Module 01-Lesson 02_Naive Bayes/01. ML in The Google Self-Driving Car-lL16AQItG1g.ar.vtt 7.21 KB
Part 11-Module 01-Lesson 09_Clustering/12. Sklearn.html 7.21 KB
Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment.html 7.21 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby.html 7.21 KB
Part 11-Module 01-Lesson 11_Text Learning/16. Text Learning Mini-Project.html 7.21 KB
Part 11-Module 01-Lesson 10_Feature Scaling/15. What Kind of Scaling.html 7.2 KB
Part 21-Module 01-Lesson 04_Functions/06. Variable Scope.html 7.2 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example.html 7.2 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.ar.vtt 7.2 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML-Ti8K9FmNW1w.pt-BR.vtt 7.19 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/04. First Principle Risk.html 7.19 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/01. Video Introduction.html 7.19 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/02. Price vs. Table Colored by Cut.html 7.19 KB
Part 09-Module 02-Lesson 01_Explore and Summarize Data/04. Evaluation and Submission.html 7.19 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview-pOxyL1lwBIw.ar.vtt 7.19 KB
Part 18-Module 04-Lesson 01_Cleaning Data/08. Address Missing Data First.html 7.19 KB
Part 05-Module 02-Lesson 02_Problem Set Data and Tables/08. Schema Match.html 7.18 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/19. Plotting with Matplotlib.html 7.18 KB
Part 18-Module 03-Lesson 01_Assessing Data/12. Data Quality Dimensions 1-5UYGvKDsd-M.en.vtt 7.18 KB
Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/10. 10. Vocabularies - Mean and SD.html 7.17 KB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/10. 23. Which Distributions.html 7.17 KB
Part 21-Module 01-Lesson 04_Functions/13. Solution Lambda Expressions.html 7.17 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/26. Empirical Confidence Intervals-ca8GQmr7B8g.ar.vtt 7.16 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/05. Fundamentals of XML.html 7.16 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/03. WARM UP - JOIN Artist to Album.html 7.16 KB
Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data-UdniaeLsViQ.ja.vtt 7.16 KB
Part 06-Module 01-Lesson 03_Analyzing Data/03. Example of Aggregation Framework.html 7.16 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution.html 7.15 KB
Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy.html 7.15 KB
Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/01. WARM UP - Sum Top 5 Subquery.html 7.15 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Video Hierarchies with Trina.html 7.15 KB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary.html 7.15 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/23. The Facebook Offering-ORLP-phGXMU.ar.vtt 7.15 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.en.vtt 7.14 KB
Part 16-Module 03-Lesson 02_SQL Joins/01. Video Motivation.html 7.14 KB
Part 05-Module 02-Lesson 03_Elements of SQL/04. Just a few SQL types.html 7.14 KB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging.html 7.14 KB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator.html 7.14 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/04. Question 3.html 7.14 KB
Part 14-Module 02-Lesson 01_Design an AB Test/01. Project Overview and Details.html 7.14 KB
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes.html 7.14 KB
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video.html 7.13 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution.html 7.13 KB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2.html 7.13 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/46. World Cup Code and Narrative Recap-lnHEvGeech0.ar.vtt 7.12 KB
Part 03-Module 01-Lesson 09_PS 3a Central Tendency/03. 3. BBC Memory Scores.html 7.12 KB
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Part 09-Module 01-Lesson 02_R Basics/09. Getting Help.html 7.12 KB
Part 06-Module 01-Lesson 03_Analyzing Data/09. Project Operator-_kupbxrZBds.pt-BR.vtt 7.11 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/img/resid-plots.gif 7.11 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team.html 7.1 KB
Part 11-Module 01-Lesson 02_Naive Bayes/18. Gaussian NB Example-wpnDwiqTCJA.ar.vtt 7.1 KB
Part 18-Module 03-Lesson 01_Assessing Data/03. Dataset Oral Insulin Clinical Trial Data-R-HT78SPxpE.pt-BR.vtt 7.1 KB
Part 18-Module 04-Lesson 01_Cleaning Data/03. Dataset Oral Insulin Clinical Trial Data -R-HT78SPxpE.pt-BR.vtt 7.1 KB
Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes.html 7.1 KB
Part 12-Module 01-Lesson 05_Interview Practice/09. Resources in Your Career Portal.html 7.1 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Data Visualization Introduction.html 7.09 KB
Part 06-Module 01-Lesson 03_Analyzing Data/13. Group Accumulation Operators.html 7.09 KB
Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning.html 7.09 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame.html 7.08 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame.html 7.08 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-xOSypbjALh4.zh-CN.vtt 7.08 KB
Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/10. Local Query - Below Average Song Lengths.html 7.08 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping.html 7.08 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/07. Correlation - price and depth.html 7.08 KB
Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit.html 7.07 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel-L2NEk4jvlcY.en.vtt 7.07 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types.html 7.07 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/19. More Tableau Practice.html 7.07 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types.html 7.07 KB
Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/13. 13. Less than -2.33.html 7.07 KB
Part 07-Module 01-Lesson 01_GitHub Review/16. Outro.html 7.07 KB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring.html 7.06 KB
Part 04-Module 01-Lesson 01_Anaconda/06. More environment actions.html 7.06 KB
Part 16-Module 01-Lesson 01_Anaconda/06. More environment actions.html 7.06 KB
Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/01. Tutorial-c3yK3OhuNvo.zh-CN.vtt 7.06 KB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words.html 7.06 KB
Part 17-Module 01-Lesson 06_Conditional Probability/16. Text Summary.html 7.06 KB
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project.html 7.06 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution.html 7.05 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. Video COALESCE.html 7.05 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/28. Server Requests and D3-Lx9dhgMZO1s.zh-CN.vtt 7.05 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/22. CHALLENGE 22. What Sample Size.html 7.05 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/08. Resources in Your Career Portal.html 7.05 KB
Part 11-Module 01-Lesson 13_PCA/28. PCA in sklearn-SBYdqlLgbGk.ar.vtt 7.05 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/01. Data Visualization Resources.html 7.05 KB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/09. 19. Deal or No Deal (Center).html 7.05 KB
Part 18-Module 04-Lesson 01_Cleaning Data/10. Solution Missing Data.html 7.05 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2.html 7.05 KB
Part 09-Module 01-Lesson 02_R Basics/10. Read and Subset Data.html 7.04 KB
Part 09-Module 01-Lesson 06_Problem Set Explore Two Variables/11. Correlations on Subsets.html 7.04 KB
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/17. 31. Skewness.html 7.04 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Video Introduction to SQL Data Cleaning.html 7.04 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2.html 7.04 KB
Part 18-Module 04-Lesson 01_Cleaning Data/06. Cleaning Sequences.html 7.04 KB
Part 18-Module 04-Lesson 01_Cleaning Data/09. Quiz Missing Data.html 7.04 KB
Part 18-Module 04-Lesson 01_Cleaning Data/13. Solution Tidiness.html 7.04 KB
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Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion.html 7.04 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Video Performance Tuning Motivation.html 7.04 KB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1.html 7.03 KB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2.html 7.03 KB
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/09. 9. Median.html 7.03 KB
Part 18-Module 04-Lesson 01_Cleaning Data/12. Quiz Tidiness.html 7.03 KB
Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.ar.vtt 7.03 KB
Part 03-Module 01-Lesson 09_PS 3a Central Tendency/10. 10. Mode.html 7.03 KB
Part 18-Module 04-Lesson 01_Cleaning Data/15. Quiz Quality.html 7.03 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Video Introduction to Advanced SQL.html 7.03 KB
Part 09-Module 01-Lesson 08_Problem Set Explore Many Variables/07. Smoothing prop_initiated vs. tenure.html 7.02 KB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video.html 7.02 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. Video What is Tableau.html 7.02 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/08. 8. Mean of Sample Means.html 7.02 KB
Part 03-Module 01-Lesson 09_PS 3a Central Tendency/08. 8. Mean.html 7.02 KB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK.html 7.02 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One.html 7.02 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/10. Summary of Principles.html 7.02 KB
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-RK6CPtXdK5Q.ar.vtt 7.02 KB
Part 14-Module 01-Lesson 06_Final Project/01. Project Instructions.html 7.02 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Video Introduction to Subqueries.html 7.02 KB
Part 11-Module 01-Lesson 08_Outliers/11. Score of Regression with Outliers.html 7.01 KB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/04. 14. Deal or No Deal (Mean vs. Median).html 7.01 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time.html 7.01 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/13. 13. Standard Error.html 7.01 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API.html 7.01 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/09. 9. Standard Error.html 7.01 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice.html 7.01 KB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm.html 7.01 KB
Part 03-Module 01-Lesson 19_PS 7 Sampling Distributions/12. 12. Mean n = 25.html 7.01 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-smBMJlpWdVI.pt-BR.vtt 7 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-smBMJlpWdVI.pt-BR.vtt 7 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/07. Question 6.html 7 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular.html 7 KB
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It.html 6.67 KB
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/01. 1. Which Distribution Is Which.html 6.3 KB
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Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging.html 6.3 KB
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Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/09. 17. Degrees of Freedom.html 6.29 KB
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names.html 6.28 KB
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/04. 10. How Old.html 6.27 KB
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Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace.html 6.27 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure.html 6.27 KB
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Part 10-Module 01-Lesson 02_LinkedIn Review/02. Resources in Your Career Portal.html 6.26 KB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/13. 20. How to Analyze Shape.html 6.25 KB
Part 06-Module 01-Lesson 03_Analyzing Data/18. Using Indexes-vL9FcO_9dCA.zh-CN.vtt 6.25 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort.html 6.25 KB
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences.html 6.24 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company.html 6.24 KB
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Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/10. 16. Heights of Bars.html 6.24 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly.html 6.23 KB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/12. 19. How to Find n.html 6.23 KB
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Part 03-Module 01-Lesson 21_PS 8a Estimation/01. 1. Point Estimates.html 6.23 KB
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Part 17-Module 01-Lesson 16_Logistic Regression/29. Model Diagnostics In Python-1Z4eorbfOOc.pt-BR.vtt 6.22 KB
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/index.html 6.22 KB
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Part 05-Module 02-Lesson 06_Problem Set Deeper Into SQL/06. Import CSV.html 6.21 KB
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Part 10-Module 01-Lesson 03_Udacity Professional Profile/06. Skills.html 6.21 KB
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/05. Iterating through Ways Tags.html 6.19 KB
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Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting.html 6.18 KB
Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/01. 1. Normal vs. t-Distribution.html 6.17 KB
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer.html 6.17 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/06. Wrapping Up.html 6.17 KB
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Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro.html 6.17 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction.html 6.17 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/24. Empirical Variability-Wzs1KFldiUE.pt-BR.vtt 6.16 KB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course.html 6.16 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work.html 6.16 KB
Part 03-Module 01-Lesson 14_PS 5a Standardizing/08. 11. Grade on a Curve.html 6.15 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search.html 6.15 KB
Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/03. 3. Alternative Hypothesis.html 6.15 KB
Part 12-Module 01-Lesson 05_Interview Practice/01. Analyzing an Interview.html 6.15 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/13. You're Ready for the Project!.html 6.15 KB
Part 05-Module 01-Lesson 06_Problem Set Data Quality/04. Other Fields.html 6.15 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/05. Question 4.html 6.15 KB
Part 17-Module 01-Lesson 07_Bayes Rule/index.html 6.15 KB
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Part 03-Module 02-Lesson 01_Test a Perceptual Phenomenon/02. Project Details.html 6.14 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary.html 6.14 KB
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/07. Question 7.html 6.14 KB
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Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/02. 2. Null Hypothesis.html 6.13 KB
Part 13-Module 01-Lesson 04_Design Principles/13. Additional Chart Types-4G-KhrIDqGA.en.vtt 6.13 KB
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Part 12-Module 02-Lesson 03_Searching and Sorting/10. Merge Sort.html 6.13 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/13. Quick Sort.html 6.13 KB
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/03. XML Design Principles-eQpSC0IFhv0.pt-BR.vtt 6.12 KB
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Part 03-Module 01-Lesson 25_PS 9b Additional Practice (Optional)/03. 12. Z-Score.html 6.12 KB
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up.html 6.12 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/05. Refining the Customer Funnel-L2NEk4jvlcY.zh-CN.vtt 6.11 KB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/06. 12. Birth Year Histogram.html 6.11 KB
Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/04. 14. SJSU Football.html 6.1 KB
Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/02. 8. IQ 125.html 6.1 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely.html 6.1 KB
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit.html 6.1 KB
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components.html 6.09 KB
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Part 12-Module 01-Lesson 05_Interview Practice/04. Query a SQL database.html 6.08 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction.html 6.08 KB
Part 05-Module 01-Lesson 05_Data Quality/10. Wikipedia Infobox Dataset-hpyNAYJODqw.en.vtt 6.07 KB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview.html 6.07 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-nXbucNJpP8I.zh-CN.vtt 6.07 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress.html 6.07 KB
Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/03. 9. IQ 150.html 6.07 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.en-US.vtt 6.07 KB
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Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers of Statistics.html 6.06 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.ar.vtt 6.06 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1.html 6.06 KB
Part 03-Module 01-Lesson 21_PS 8a Estimation/07. 8. Probability.html 6.06 KB
Part 03-Module 01-Lesson 20_L8 Estimation/index.html 6.06 KB
Part 03-Module 01-Lesson 25_PS 9b Additional Practice (Optional)/01. 10. Hypotheses.html 6.06 KB
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/04. Data Model.html 6.06 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/05. NumPy Arrays-7GeiZ8IVZfE.zh-CN.vtt 6.06 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program.html 6.05 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags.html 6.05 KB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/11. 24. Median Given Histogram.html 6.05 KB
Part 03-Module 01-Lesson 21_PS 8a Estimation/04. 4. Increase Population SD.html 6.04 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/index.html 6.04 KB
Part 05-Module 01-Lesson 05_Data Quality/11. Auditing a Cross-Field Constraint-Y7TNXALXut8.en.vtt 6.04 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/02. Familiarize Yourself with the Dataset-JyX6j00Q2Cg.pt-BR.vtt 6.04 KB
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Part 03-Module 01-Lesson 21_PS 8a Estimation/03. 3. Increase Sample Size.html 6.04 KB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data.html 6.03 KB
Part 03-Module 01-Lesson 32_PS 11b Additional Practice (Optional)/08. 13. Decision.html 6.03 KB
Part 04-Module 01-Lesson 01_Anaconda/01. Introduction.html 6.03 KB
Part 16-Module 01-Lesson 01_Anaconda/01. Introduction.html 6.03 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro.html 6.02 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely.html 6.02 KB
Part 03-Module 01-Lesson 21_PS 8a Estimation/06. 7. Standard Error.html 6.01 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection.html 6.01 KB
Part 21-Module 01-Lesson 05_Scripting/index.html 6.01 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network.html 6.01 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components.html 6.01 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/20. Duration vs. Exposure-MsByTo7FRgs.en.vtt 6.01 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure.html 6.01 KB
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Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.ar.vtt 6 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/11. Question 10.html 6 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction.html 6 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components.html 6 KB
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Part 04-Module 01-Lesson 02_Jupyter notebooks/05. Code cells.html 5.99 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations.html 5.99 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/index.html 5.98 KB
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Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion.html 5.98 KB
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Part 03-Module 01-Lesson 14_PS 5a Standardizing/03. 3. OkCupid.html 5.98 KB
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Part 03-Module 01-Lesson 21_PS 8a Estimation/08. 9. Margin of Error.html 5.98 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/25. Empirical Variability Sanity Checking-6vxdVWIA6dI.zh-CN.vtt 5.97 KB
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/10. Welcome to the end of the lesson.html 5.96 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.ar.vtt 5.96 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/08. Coding 2.html 5.96 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.ar.vtt 5.96 KB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles.html 5.96 KB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations.html 5.96 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.ar.vtt 5.96 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare.html 5.95 KB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview.html 5.95 KB
Part 21-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.pt-BR.vtt 5.95 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -nZq-Y2lfjpY.en.vtt 5.95 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-WmJKPUthUPw.en.vtt 5.94 KB
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Part 16-Module 03-Lesson 03_SQL Aggregations/index.html 5.94 KB
Part 03-Module 01-Lesson 14_PS 5a Standardizing/10. 13. SD.html 5.94 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites.html 5.93 KB
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection.html 5.93 KB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction.html 5.93 KB
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/index.html 5.93 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.ar.vtt 5.93 KB
Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-cXluuqCVg18.en.vtt 5.93 KB
Part 04-Module 03-Lesson 01_Investigate a Dataset/04. Project Workspace Complete and Submit Project.html 5.93 KB
Part 14-Module 01-Lesson 05_Analyzing Results/07. Sanity Checking Wrapup-rCAYdZk5O2E.en.vtt 5.93 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/01. Introduction.html 5.93 KB
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure.html 5.92 KB
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection.html 5.92 KB
Part 03-Module 01-Lesson 21_PS 8a Estimation/09. 10. 95 CI.html 5.92 KB
Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/09. 9. Type I Error.html 5.91 KB
Part 03-Module 01-Lesson 21_PS 8a Estimation/05. 6. Critical Values 95 CI.html 5.91 KB
Part 05-Module 02-Lesson 02_Problem Set Data and Tables/02. WARM UP - Translate Query #1.html 5.91 KB
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Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys.html 5.91 KB
Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph.html 5.91 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure.html 5.91 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.ar.vtt 5.91 KB
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Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.ar.vtt 4.6 KB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.ar.vtt 4.6 KB
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Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.ar.vtt 4.59 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-aejs122BTzA.zh-CN.vtt 4.59 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.ar.vtt 4.58 KB
Part 18-Module 02-Lesson 01_Gathering Data/06. Flat File Structure-bLKVRIhrZUY.zh-CN.vtt 4.58 KB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.ar.vtt 4.58 KB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.en.vtt 4.58 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2-ZXy8jgywY5g.zh-CN.vtt 4.57 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.ar.vtt 4.57 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.ar.vtt 4.57 KB
Part 13-Module 01-Lesson 07_Narrative Structures/02. Approaches to Journalism-AxFSDfKP7Zs.pt-BR.vtt 4.57 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/08. Auditing Street Names-c0IcUiF_kXs.zh-CN.vtt 4.57 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/09. Auditing Street Names-c0IcUiF_kXs.zh-CN.vtt 4.57 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.ar.vtt 4.56 KB
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Part 17-Module 01-Lesson 06_Conditional Probability/index.html 4.56 KB
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Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.zh-CN.vtt 4.55 KB
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Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/index.html 4.54 KB
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Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.pt-BR.vtt 4.54 KB
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Part 15-Module 01-Lesson 02_Design Principles/img/strip-plot.png 4.53 KB
Part 03-Module 01-Lesson 27_PS 10a t-Tests, Part 1/index.html 4.53 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/index.html 4.53 KB
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Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.ja.vtt 4.53 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.ar.vtt 4.53 KB
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Part 13-Module 01-Lesson 04_Design Principles/06. Common Chart Types-xD2_AU6atqA.zh-CN.vtt 4.52 KB
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Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.ar.vtt 4.52 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.pt-BR.vtt 4.52 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-HGYW-skXvY4.zh-CN.vtt 4.52 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-QoEqPotgMbA.en.vtt 4.52 KB
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Part 03-Module 01-Lesson 17_PS 6 Normal Distribution/index.html 4.52 KB
Part 03-Module 01-Lesson 10_PS 3b Additional Practice (Optional)/index.html 4.51 KB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.ar.vtt 4.51 KB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-TIgfjmp-4BA.pt-BR.vtt 4.51 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.ar.vtt 4.51 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/02. Metric Definition Overview-pOxyL1lwBIw.zh-CN.vtt 4.51 KB
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Part 17-Module 01-Lesson 05_Binomial Distribution/index.html 4.51 KB
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/index.html 4.51 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.ar.vtt 4.51 KB
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/index.html 4.5 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.pt-BR.vtt 4.5 KB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.pt-BR.vtt 4.5 KB
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Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.ar.vtt 4.5 KB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.ar.vtt 4.49 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/04. Consistency of Diversion-im8-LLU5J_Y.zh-CN.vtt 4.49 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-O9d9dKyHtIc.zh-CN.vtt 4.49 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.ar.vtt 4.48 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.en.vtt 4.48 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.ar.vtt 4.48 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.ar.vtt 4.48 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 2-W2tL3QSBi3k.en.vtt 4.47 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.pt-BR.vtt 4.47 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.en.vtt 4.47 KB
Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.pt-BR.vtt 4.47 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/06. A Problem and How You Dealt With It-7IKqdW30GvQ.zh-CN.vtt 4.47 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.ar.vtt 4.47 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/index.html 4.47 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.pt-BR.vtt 4.46 KB
Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.pt-BR.vtt 4.46 KB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-5571wc0iWCI.zh-CN.vtt 4.46 KB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.ar.vtt 4.45 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.ar.vtt 4.45 KB
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Part 13-Module 01-Lesson 08_Animation and Interaction/05. Lets Make a Map-mOZuq2JoN-k.zh-CN.vtt 4.45 KB
Part 03-Module 01-Lesson 31_PS 11a t-Tests, Part 3/index.html 4.45 KB
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Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.en.vtt 4.44 KB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.ar.vtt 4.44 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/index.html 4.43 KB
Part 21-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.pt-BR.vtt 4.43 KB
Part 14-Module 01-Lesson 05_Analyzing Results/15. Multiple Metrics Example 3-XByoblkCgfE.zh-CN.vtt 4.43 KB
Part 14-Module 01-Lesson 05_Analyzing Results/18. Gotchas Changes Over Time-P7Hso-EoWvA.zh-CN.vtt 4.43 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.ja.vtt 4.42 KB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.ar.vtt 4.42 KB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.ar.vtt 4.42 KB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.ar.vtt 4.42 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.en-US.vtt 4.42 KB
Part 05-Module 02-Lesson 04_Problem Set Elements of SQL/index.html 4.42 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.en.vtt 4.42 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.pt-BR.vtt 4.42 KB
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Part 17-Module 01-Lesson 03_Admissions Case Study/index.html 4.41 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/index.html 4.41 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/index.html 4.41 KB
Part 18-Module 02-Lesson 01_Gathering Data/11. Flashforward 1-Sr5v0i9m_sw.zh-CN.vtt 4.41 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.ar.vtt 4.41 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/04. Meet Chris-0ccflD9x5WU.zh-CN.vtt 4.41 KB
Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.pt-BR.vtt 4.4 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/09. Metric Choice-BeIy4A6YKrY.pt-BR.vtt 4.4 KB
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Part 11-Module 01-Lesson 14_Validation/10. Practical Advice for K-Fold in sklearn-COVRSk0GDEE.zh-CN.vtt 4.4 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/31. Layout and Scales-BQWN9ImjUFE.zh-CN.vtt 4.4 KB
Part 03-Module 01-Lesson 14_PS 5a Standardizing/index.html 4.4 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/index.html 4.4 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.ar.vtt 4.4 KB
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-spVqFnSvlIU.en.vtt 4.4 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/29. Collecting Participating Countries-ha6kGtT9XMQ.ar.vtt 4.4 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.ar.vtt 4.4 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.ar.vtt 4.39 KB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.ar.vtt 4.39 KB
Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.pt-BR.vtt 4.39 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.ar.vtt 4.39 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.ar.vtt 4.39 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/15. Filtering and Segmenting Example-WgM3cBEtkqg.en.vtt 4.39 KB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.ar.vtt 4.38 KB
Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.en.vtt 4.38 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/22. How Page Views Affect Sensitivity-WFVj8QI_uto.en.vtt 4.38 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.ar.vtt 4.38 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.ar.vtt 4.38 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.ar.vtt 4.38 KB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.ar.vtt 4.38 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.zh-CN.vtt 4.38 KB
Part 09-Module 01-Lesson 03_Explore One Variable/22. Transforming Data-0L3Obq4FSVQ.ja.vtt 4.37 KB
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Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.ar.vtt 4.37 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.zh-CN.vtt 4.37 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/index.html 4.37 KB
Part 18-Module 02-Lesson 01_Gathering Data/16. JSON File Structure-hO2CayzZBoA.zh-CN.vtt 4.37 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.ar.vtt 4.37 KB
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Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.ar.vtt 4.36 KB
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Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.ar.vtt 4.36 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.ar.vtt 4.35 KB
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Part 03-Module 01-Lesson 09_PS 3a Central Tendency/index.html 4.35 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/04. Load D3 in the JavaScript Console-mGyo6dOf0So.zh-CN.vtt 4.35 KB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-4GBJk6R0pb4.zh-CN.vtt 4.35 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.en.vtt 4.34 KB
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Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-60IGcSho56o.pt-BR.vtt 4.34 KB
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Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.pt-BR.vtt 4.34 KB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.en.vtt 4.34 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.ar.vtt 4.33 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-Zdl01HMSjTw.pt-BR.vtt 4.33 KB
Part 15-Module 01-Lesson 02_Design Principles/img/lie-factor.png 4.33 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/index.html 4.33 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/index.html 4.33 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.pt-BR.vtt 4.32 KB
Part 10-Module 01-Lesson 03_Udacity Professional Profile/index.html 4.32 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.ar.vtt 4.32 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.pt-BR.vtt 4.32 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/index.html 4.32 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.ar.vtt 4.32 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-bq_gVndUj1U.pt-BR.vtt 4.32 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.en.vtt 4.31 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/24. Lessons Learned-GonjL0GbNiw.zh-CN.vtt 4.31 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.en.vtt 4.31 KB
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Part 12-Module 02-Lesson 06_Graphs/index.html 4.31 KB
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Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/06. Iterating through Ways Tags-GYhOEJ8EXkg.zh-CN.vtt 4.27 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.en.vtt 4.27 KB
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Part 05-Module 01-Lesson 05_Data Quality/15. Auditing Completeness-PMbcv9AYQT4.en.vtt 4.26 KB
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Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.en.vtt 4.25 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.ar.vtt 4.24 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.ar.vtt 4.24 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.ar.vtt 4.23 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.en.vtt 4.23 KB
Part 14-Module 01-Lesson 06_Final Project/index.html 4.23 KB
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Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.en-US.vtt 4.23 KB
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Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.ar.vtt 4.22 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.en.vtt 4.22 KB
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Part 12-Module 02-Lesson 02_List-Based Collections/index.html 4.19 KB
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Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.ar.vtt 4.18 KB
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Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.ja.vtt 4.18 KB
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Part 12-Module 02-Lesson 05_Trees/06. Depth-First Traversals-wp5ohHFTieM.en.vtt 4.17 KB
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Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.zh-CN.vtt 4.17 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.ar.vtt 4.17 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.ar.vtt 4.17 KB
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Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.ar.vtt 4.16 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.ar.vtt 4.16 KB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.ar.vtt 4.16 KB
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Part 03-Module 01-Lesson 21_PS 8a Estimation/index.html 4.15 KB
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Part 11-Module 01-Lesson 13_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.en.vtt 4.15 KB
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Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.ar.vtt 4.14 KB
Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.en.vtt 4.14 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.ar.vtt 4.13 KB
Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.ar.vtt 4.13 KB
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Part 09-Module 02-Lesson 01_Explore and Summarize Data/index.html 4.13 KB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.ar.vtt 4.13 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/05. Brainstorming-LJFYhMDCCsU.pt-BR.vtt 4.13 KB
Part 21-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.ar.vtt 4.13 KB
Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.en-US.vtt 4.12 KB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.en-US.vtt 4.12 KB
Part 04-Module 03-Lesson 01_Investigate a Dataset/index.html 4.12 KB
Part 13-Module 01-Lesson 06_Problem Set Chart Types and Axes/13. Scott's Advice to Break into Data Vis-v5ywQMRCxMg.zh-CN.vtt 4.12 KB
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/index.html 4.12 KB
Part 12-Module 02-Lesson 02_List-Based Collections/06. Linked Lists in Depth-ZONGA5wmREI.en.vtt 4.12 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.ar.vtt 4.12 KB
Part 11-Module 01-Lesson 07_Regressions/19. Extracting Information from sklearn-zDIRQE_oxfk.en.vtt 4.12 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.en-US.vtt 4.12 KB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.pt-BR.vtt 4.12 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-nqi4oT2aeAw.en.vtt 4.12 KB
Part 09-Module 01-Lesson 01_What is EDA/index.html 4.12 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/14. Efficiency of Quick Sort-aMb5GHPGQ1U.zh-CN.vtt 4.11 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.ar.vtt 4.11 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.pt-BR.vtt 4.11 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-w6CLWh1dLCU.en.vtt 4.11 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/06. Flexible Schema-6a-YgbrEACk.en.vtt 4.11 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.ar.vtt 4.11 KB
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Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.pt-BR.vtt 4.1 KB
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Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.en.vtt 4.1 KB
Part 07-Module 01-Lesson 01_GitHub Review/13. Interview with Art - Part 3-M6PKr3S1rPg.en.vtt 4.1 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.ar.vtt 4.1 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.pt-BR.vtt 4.09 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/index.html 4.09 KB
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Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.en.vtt 4.09 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/25. Correlation Does Not Imply Causation-aeEhfjPFiCw.zh-CN.vtt 4.09 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.ar.vtt 4.09 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/02. Case Study US Unemployment-R6Nk8NsEzUA.en.vtt 4.09 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import-tU1N-8aNB_M.en.vtt 4.09 KB
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Part 03-Module 01-Lesson 15_PS 5b Additional Practice (Optional)/index.html 4.09 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.ar.vtt 4.08 KB
Part 03-Module 01-Lesson 24_PS 9a Hypothesis Testing/index.html 4.08 KB
Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.en.vtt 4.08 KB
Part 17-Module 01-Lesson 08_Python Probability Practice/index.html 4.08 KB
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/05. NumPy and Pandas Data Types-seEFuJ-qvlg.en.vtt 4.08 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/05. NumPy and Pandas Data Types-seEFuJ-qvlg.en.vtt 4.08 KB
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Part 11-Module 01-Lesson 07_Regressions/31. R Squared in SKlearn-Dxf1I4IE6co.zh-CN.vtt 4.07 KB
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Part 09-Module 01-Lesson 01_What is EDA/08. Aude Explores Coordinated Migration-7ihp6ofAJG8.zh-CN.vtt 4.05 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.en.vtt 4.05 KB
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/15. Extracting Entities-aJD8WJa3-9A.zh-CN.vtt 4.04 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/index.html 4.04 KB
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Part 17-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.pt-BR.vtt 4.04 KB
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Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.en.vtt 4.01 KB
Part 04-Module 01-Lesson 01_Anaconda/index.html 4 KB
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Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.pt-BR.vtt 4 KB
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Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.ar.vtt 3.98 KB
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.ar.vtt 3.98 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.ar.vtt 3.98 KB
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Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.en.vtt 3.97 KB
Part 20-Module 01-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.zh-CN.vtt 3.97 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/46. Inspecting Data with Functions--itFNdnc5ns.zh-CN.vtt 3.96 KB
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Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.ja.vtt 3.96 KB
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Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.ar.vtt 3.95 KB
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Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.ar.vtt 3.94 KB
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Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.ar.vtt 3.94 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.en.vtt 3.94 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.en.vtt 3.94 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.ar.vtt 3.93 KB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.zh-CN.vtt 3.93 KB
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Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.ar.vtt 3.93 KB
Part 21-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.zh-CN.vtt 3.93 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.ar.vtt 3.93 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.pt-BR.vtt 3.93 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.pt-BR.vtt 3.93 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.ar.vtt 3.92 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.ar.vtt 3.92 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/38. Communicating Your Message-wZt6fXEUqQM.pt-BR.vtt 3.92 KB
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Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.pt-BR.vtt 3.92 KB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.ar.vtt 3.92 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.en.vtt 3.92 KB
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Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.ar.vtt 3.92 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.en.vtt 3.92 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.en.vtt 3.91 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.pt-BR.vtt 3.91 KB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.pt-BR.vtt 3.91 KB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.en.vtt 3.91 KB
Part 05-Module 01-Lesson 06_Problem Set Data Quality/index.html 3.91 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.en.vtt 3.91 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.en.vtt 3.91 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.ar.vtt 3.9 KB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.ar.vtt 3.9 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. 03 Tableau Interface-q3E4CCYeIyM.en.vtt 3.9 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.ar.vtt 3.9 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/04. 29 Number Summary-gzUN5zKLHjQ.pt-BR.vtt 3.9 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-6UYEM0XUSGQ.zh-CN.vtt 3.9 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.ar.vtt 3.9 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.pt-BR.vtt 3.9 KB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.ar.vtt 3.9 KB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.ar.vtt 3.89 KB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.pt-BR.vtt 3.89 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.ar.vtt 3.89 KB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-cy8BwWl36Q4.zh-CN.vtt 3.89 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-MLzRdgcFYQQ.zh-CN.vtt 3.89 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.ar.vtt 3.89 KB
Part 05-Module 01-Lesson 04_Problem Set Data in More Complex Formats/index.html 3.89 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.ar.vtt 3.89 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.en-US.vtt 3.89 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.pt-BR.vtt 3.89 KB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.en.vtt 3.88 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.pt-BR.vtt 3.88 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/36. Groups And Sets-Yb-91NVNgTA.zh-CN.vtt 3.88 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.en.vtt 3.88 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.ar.vtt 3.88 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-FORb9Tja-p0.zh-CN.vtt 3.88 KB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.ar.vtt 3.88 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.ar.vtt 3.88 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.ar.vtt 3.88 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/10. Worst Case and Approximation-ZYcmui02J40.zh-CN.vtt 3.88 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.en.vtt 3.88 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.en.vtt 3.87 KB
Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.en-US.vtt 3.87 KB
Part 05-Module 03-Lesson 01_Wrangle OpenStreetMap Data/index.html 3.87 KB
Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.en.vtt 3.87 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.pt-BR.vtt 3.87 KB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.en.vtt 3.87 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/index.html 3.86 KB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.ar.vtt 3.86 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.ar.vtt 3.86 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.ar.vtt 3.86 KB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.ar.vtt 3.86 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.ar.vtt 3.85 KB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.ar.vtt 3.85 KB
Part 12-Module 02-Lesson 06_Graphs/02. What Is a Graph-p-_DFOyEMV8.pt-BR.vtt 3.85 KB
Part 13-Module 01-Lesson 05_Dimple.js/30. EDA vs Sketching Data Visualizations-hFlVFyatBF0.zh-CN.vtt 3.85 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/06. Collisions-BUaWIjZ_ToY.pt-BR.vtt 3.85 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.pt-BR.vtt 3.85 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.pt-BR.vtt 3.85 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.en.vtt 3.85 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.en.vtt 3.85 KB
Part 13-Module 02-Lesson 01_Make Effective Data Visualization/index.html 3.85 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/02. Standard Error-GTsnxTCjmcM.zh-CN.vtt 3.84 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.zh-CN.vtt 3.84 KB
Part 12-Module 01-Lesson 05_Interview Practice/06. Design a Spam Classifier-Uy89Ff49pRc.zh-CN.vtt 3.84 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/04. Meet the Careers Team-cuKecPpZ7PM.pt-BR.vtt 3.83 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/03. Data Analysis Process-cAceF0h4vpI.zh-CN.vtt 3.83 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/26. DATE Functions Part II-UPWkDhW4cLI.zh-CN.vtt 3.83 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.ar.vtt 3.83 KB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.pt-BR.vtt 3.83 KB
Part 11-Module 02-Lesson 01_Identify Fraud from Enron Email/index.html 3.83 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/05. 03 Tableau Interface-q3E4CCYeIyM.zh-CN.vtt 3.83 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.en.vtt 3.83 KB
Part 10-Module 01-Lesson 02_LinkedIn Review/index.html 3.83 KB
Part 02-Module 02-Lesson 01_Project Prep/index.html 3.83 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.ar.vtt 3.83 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.ar.vtt 3.83 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-ycbXO4xBEVw.zh-CN.vtt 3.82 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.pt-BR.vtt 3.82 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.pt-BR.vtt 3.82 KB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.en.vtt 3.82 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.ar.vtt 3.82 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.ar.vtt 3.82 KB
Part 03-Module 02-Lesson 01_Test a Perceptual Phenomenon/index.html 3.82 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.ar.vtt 3.81 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.en.vtt 3.81 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.pt-BR.vtt 3.81 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.pt-BR.vtt 3.81 KB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-FDSmlIBy7ko.en.vtt 3.81 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.ar.vtt 3.81 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.pt-BR.vtt 3.81 KB
Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.en.vtt 3.81 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. 05 Hierarchies-vkHeQcI08yc.en.vtt 3.81 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.en.vtt 3.81 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.ar.vtt 3.81 KB
Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.en.vtt 3.8 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.ar.vtt 3.79 KB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.en.vtt 3.79 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.en.vtt 3.79 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-uoHzcmf4yXU.zh-CN.vtt 3.79 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.pt-BR.vtt 3.79 KB
Part 09-Module 01-Lesson 01_What is EDA/03. Why learn EDA-YM68DrqJw1I.zh-CN.vtt 3.79 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/22. Looking at Samples of Households-kQePh6UTB90.ja.vtt 3.79 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.zh-CN.vtt 3.79 KB
Part 19-Module 01-Lesson 02_Design/09. Design Integrity-y72_fVFtqlY.zh-CN.vtt 3.78 KB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5DvUOwA7xhU.zh-CN.vtt 3.78 KB
Part 12-Module 01-Lesson 03_Interview Fails/index.html 3.78 KB
Part 14-Module 01-Lesson 05_Analyzing Results/17. Drawing Conclusions-CZQ-nZyUG7g.zh-CN.vtt 3.78 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.pt-BR.vtt 3.78 KB
Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.pt-BR.vtt 3.78 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/11. Dummy Variable Interpretation-TxP_TD0kbOo.zh-CN.vtt 3.77 KB
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Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.en.vtt 3.57 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.ar.vtt 3.57 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.pt-BR.vtt 3.57 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.en.vtt 3.56 KB
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Part 11-Module 01-Lesson 14_Validation/03. TrainTest Split in sklearn-lSwvUmZCvco.zh-CN.vtt 3.56 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.ar.vtt 3.56 KB
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.pt-BR.vtt 3.56 KB
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Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.en-US.vtt 3.55 KB
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Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.en.vtt 3.55 KB
Part 14-Module 01-Lesson 05_Analyzing Results/10. Single Metric Gotchas-WrfWFLiFeMU.zh-CN.vtt 3.54 KB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.en.vtt 3.54 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.pt-BR.vtt 3.54 KB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.ja.vtt 3.54 KB
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Part 09-Module 01-Lesson 03_Explore One Variable/21. Lada's Money Bag Meme-Isa_FGQrvgs.zh-CN.vtt 3.54 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.en.vtt 3.54 KB
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Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/13. Worksheets-2xRKvQTRtlk.zh-CN.vtt 3.54 KB
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Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.en.vtt 3.53 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.en.vtt 3.53 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.en.vtt 3.53 KB
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Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.zh-CN.vtt 3.52 KB
Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.zh-CN.vtt 3.52 KB
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.ar.vtt 3.52 KB
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Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.ar.vtt 3.52 KB
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Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.en.vtt 3.51 KB
Part 13-Module 01-Lesson 07_Narrative Structures/28. Joins in D3-rDjOINfKftY.zh-CN.vtt 3.51 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.pt-BR.vtt 3.51 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.pt-BR.vtt 3.51 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.en-US.vtt 3.51 KB
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Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.pt-BR.vtt 3.51 KB
Part 13-Module 01-Lesson 05_Dimple.js/29. From Bars to Circles to Lines-MA-n0Hi3Wyg.zh-CN.vtt 3.51 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/20. Practical, or Substantive, Significance-Q576t5aaZ34.zh-CN.vtt 3.51 KB
Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.pt-BR.vtt 3.5 KB
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.en.vtt 3.5 KB
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Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.pt-BR.vtt 3.5 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.ar.vtt 3.5 KB
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/14. What is the Question-xQJyObqxg3E.zh-CN.vtt 3.5 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/17. Sizing Example-f69Hs7m1axc.zh-CN.vtt 3.5 KB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.en-US.vtt 3.49 KB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.en.vtt 3.49 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.en.vtt 3.49 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/07. History of AB Testing-NNiKGao0xnk.zh-CN.vtt 3.49 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.ar.vtt 3.49 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.en.vtt 3.49 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.en.vtt 3.48 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.pt-BR.vtt 3.48 KB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.th.vtt 3.48 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.pt-BR.vtt 3.48 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.pt-BR.vtt 3.48 KB
Part 03-Module 01-Lesson 07_Google Spreadsheet Tutorial/index.html 3.48 KB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.ar.vtt 3.48 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.ar.vtt 3.48 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/01. Intro-UJyJm79RS88.zh-CN.vtt 3.48 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.pt-BR.vtt 3.48 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/20. Hierarchies-wl_AM-spH68.zh-CN.vtt 3.48 KB
Part 12-Module 01-Lesson 04_Land a Job Offer/index.html 3.47 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.ar.vtt 3.47 KB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.en.vtt 3.47 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.en.vtt 3.47 KB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment -BNRJdhA8_s8.zh-CN.vtt 3.47 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.pt-BR.vtt 3.47 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.pt-BR.vtt 3.47 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.pt-BR.vtt 3.47 KB
Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.en.vtt 3.47 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML Structure-UjCbXQ8Coic.zh-CN.vtt 3.47 KB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.en.vtt 3.47 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.en.vtt 3.47 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.ar.vtt 3.47 KB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.it.vtt 3.47 KB
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Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.en.vtt 3.46 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.en.vtt 3.46 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.en.vtt 3.46 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.pt-BR.vtt 3.46 KB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.en.vtt 3.46 KB
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.ar.vtt 3.46 KB
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Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.pt-BR.vtt 3.46 KB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.ja.vtt 3.46 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-8zWQmAVPthY.zh-CN.vtt 3.46 KB
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Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.pt-BR.vtt 3.46 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-8zWQmAVPthY.zh-CN.vtt 3.46 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/19. Exists-j5l5UvE3Odw.zh-CN.vtt 3.45 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.en.vtt 3.45 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.it.vtt 3.45 KB
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Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.en.vtt 3.44 KB
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Part 05-Module 02-Lesson 05_Deeper into SQL/03. Normalized Design Part Two-l6SDnhM7B_k.zh-CN.vtt 3.43 KB
Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.ar.vtt 3.43 KB
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Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-krV6r7HxmZU.zh-CN.vtt 3.42 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.es.vtt 3.42 KB
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Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.ar.vtt 3.42 KB
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Part 21-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.en.vtt 3.42 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.en.vtt 3.42 KB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.ar.vtt 3.42 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-E3NhvAC3Ghw.ja.vtt 3.42 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.pt-BR.vtt 3.41 KB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.es-ES.vtt 3.41 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/08. Report Results-xNbzHOnSx5Q.zh-CN.vtt 3.41 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.ar.vtt 3.41 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/08. Notation Intro-xHwIU4j3gBc.zh-CN.vtt 3.41 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.ar.vtt 3.41 KB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.pt-BR.vtt 3.41 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.pt-BR.vtt 3.41 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/02. Elevator Pitch-S-nAHPrkQrQ.zh-CN.vtt 3.4 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.ar.vtt 3.4 KB
Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.pt-BR.vtt 3.4 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.ar.vtt 3.4 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.en-US.vtt 3.4 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.ar.vtt 3.4 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.en.vtt 3.4 KB
Part 05-Module 02-Lesson 01_Data and Tables/12. Related Tables-lMwSjDYgCq0.zh-CN.vtt 3.4 KB
Part 07-Module 01-Lesson 01_GitHub Review/04. Interview with Art - Part 1-ClLYamtaO-Q.zh-CN.vtt 3.4 KB
Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.pt-BR.vtt 3.4 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.en.vtt 3.4 KB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.pt-BR.vtt 3.39 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.pt-BR.vtt 3.39 KB
Part 13-Module 01-Lesson 05_Dimple.js/16. Debugging and Inspecting Chart Objects-XYMtkn0DyIM.zh-CN.vtt 3.39 KB
Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.pt-BR.vtt 3.39 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.pt-BR.vtt 3.39 KB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.pt-BR.vtt 3.39 KB
Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.pt-BR.vtt 3.39 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.en.vtt 3.39 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.en.vtt 3.39 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.pt-BR.vtt 3.39 KB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-Tx_jtCfrbt0.en.vtt 3.39 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/08. Exact and Approximate Algorithms-3A8YqOYlAwQ.zh-CN.vtt 3.39 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.ar.vtt 3.39 KB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.th.vtt 3.38 KB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.ar.vtt 3.38 KB
Part 11-Module 01-Lesson 11_Text Learning/11. Stemming with NLTK-gWbkW_cyNs8.zh-CN.vtt 3.38 KB
Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.en-US.vtt 3.38 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.en.vtt 3.38 KB
Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.pt-BR.vtt 3.38 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.en.vtt 3.38 KB
Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.en.vtt 3.38 KB
Part 18-Module 02-Lesson 01_Gathering Data/20. Flashforward 2-Sbyn8aT-8G8.zh-CN.vtt 3.38 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.pt-BR.vtt 3.38 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.ar.vtt 3.38 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.pt-BR.vtt 3.38 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.en.vtt 3.38 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.pt-BR.vtt 3.38 KB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.ar.vtt 3.38 KB
Part 09-Module 01-Lesson 02_R Basics/04. Install RStudio on Windows-5ZbjUEg4a1g.en.vtt 3.38 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.pt-BR.vtt 3.38 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.ar.vtt 3.38 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.pt-BR.vtt 3.38 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.en.vtt 3.37 KB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.pt-BR.vtt 3.37 KB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.en.vtt 3.37 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.pt-BR.vtt 3.37 KB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.ar.vtt 3.37 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.pt-BR.vtt 3.36 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.ar.vtt 3.36 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.en.vtt 3.36 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/13. Pandas Series-V7zAB9dUaFY.en.vtt 3.36 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.pt-BR.vtt 3.36 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.pt-BR.vtt 3.36 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.es.vtt 3.36 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.es.vtt 3.36 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-GXT_vXBA0vQ.en.vtt 3.36 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.pt-BR.vtt 3.36 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/02. What Is A POI-wDQhif-MWuY.zh-CN.vtt 3.36 KB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.ja.vtt 3.36 KB
Part 11-Module 01-Lesson 12_Feature Selection/14. Balancing Error with Number of Features-IwiIFMcDwoA.zh-CN.vtt 3.36 KB
Part 05-Module 02-Lesson 01_Data and Tables/15. Joining Tables-lXoiI0gx3MU.zh-CN.vtt 3.35 KB
Part 13-Module 01-Lesson 07_Narrative Structures/43. D3 Parsing Dates and Times-DrOoJJWRAno.en.vtt 3.35 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.ar.vtt 3.35 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.pt-BR.vtt 3.35 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.pt-BR.vtt 3.35 KB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.pt-BR.vtt 3.35 KB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.ar.vtt 3.35 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.ja.vtt 3.35 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/16. Sizing Overview-sKRWt_iS7zo.en.vtt 3.35 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.pt-BR.vtt 3.35 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.zh-CN.vtt 3.35 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/05. A Faster Algorithm-J7S3CHFBZJA.zh-CN.vtt 3.35 KB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.pt-BR.vtt 3.35 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.th.vtt 3.35 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-YaZu4waSryo.en.vtt 3.35 KB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.pt-BR.vtt 3.35 KB
Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.pt-BR.vtt 3.34 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.en.vtt 3.34 KB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.en.vtt 3.34 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.en.vtt 3.34 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.ar.vtt 3.34 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.ar.vtt 3.34 KB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.ar.vtt 3.34 KB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.ar.vtt 3.33 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.en.vtt 3.33 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/11. Other Techniques Example-sOGuF3it6Ek.zh-CN.vtt 3.33 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.pt-BR.vtt 3.33 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/20. Regex Operator-MbJfmI7kzQI.zh-CN.vtt 3.33 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.pt-BR.vtt 3.33 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.en.vtt 3.33 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.ar.vtt 3.33 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.en.vtt 3.33 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/13. Getting Data into MongoDB-hi6g1NE3sPk.zh-CN.vtt 3.33 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/29. Removing Documents-oFWNOvxuIRQ.en.vtt 3.33 KB
Part 05-Module 02-Lesson 01_Data and Tables/13. Uniqueness and Keys-TIayTr4y9RA.zh-CN.vtt 3.32 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.ar.vtt 3.32 KB
Part 13-Module 01-Lesson 05_Dimple.js/01. Dimple Interlude-bo8_lJucTPI.en.vtt 3.32 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.en.vtt 3.32 KB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.en.vtt 3.32 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.en.vtt 3.32 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.pt-BR.vtt 3.32 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/17. Range Queries-6r5Xc-_lhEI.zh-CN.vtt 3.32 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.en.vtt 3.32 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.pt-BR.vtt 3.32 KB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.en.vtt 3.32 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.es.vtt 3.31 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.en.vtt 3.31 KB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.pt-BR.vtt 3.31 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.pt-BR.vtt 3.31 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.ar.vtt 3.31 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.en.vtt 3.31 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-fo4MJMkwhYU.pt-BR.vtt 3.31 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.ar.vtt 3.31 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.en.vtt 3.31 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.ar.vtt 3.31 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.pt-BR.vtt 3.31 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.en.vtt 3.31 KB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.ja.vtt 3.31 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1-mUfrDUEEa_k.zh-CN.vtt 3.31 KB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.en.vtt 3.31 KB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.ar.vtt 3.3 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.ar.vtt 3.3 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.en.vtt 3.3 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/01. Welcome to the DA Nanodegree Program-FKcIJkTA3GI.zh-CN.vtt 3.3 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.en.vtt 3.3 KB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.pt-BR.vtt 3.3 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/14. Writing Code with DB API-Zd0PAgb6vY4.zh-CN.vtt 3.3 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.pt-BR.vtt 3.3 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-KSZ2XLYk4hk.en.vtt 3.3 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-KSZ2XLYk4hk.en.vtt 3.3 KB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.pt-BR.vtt 3.3 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.en-US.vtt 3.3 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-74mudn321tA.en.vtt 3.3 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.ar.vtt 3.3 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.ar.vtt 3.3 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-CPDMSJEH16s.zh-CN.vtt 3.3 KB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.pt-BR.vtt 3.3 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.en.vtt 3.29 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-qgwygpD0eN8.en.vtt 3.29 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.ar.vtt 3.29 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.en.vtt 3.29 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.pt-BR.vtt 3.29 KB
Part 11-Module 01-Lesson 07_Regressions/27. Problem with Minimizing Absolute Errors-U46D7oEijlI.zh-CN.vtt 3.29 KB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.pt-BR.vtt 3.29 KB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.en-US.vtt 3.29 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.pt-BR.vtt 3.29 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.zh-CN.vtt 3.29 KB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.ja.vtt 3.29 KB
Part 21-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.zh-CN.vtt 3.29 KB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.en.vtt 3.29 KB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.en.vtt 3.29 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.ar.vtt 3.29 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/28. Multi Update-tuXc0Ycy_yM.zh-CN.vtt 3.29 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.en-US.vtt 3.29 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.ar.vtt 3.29 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.ar.vtt 3.29 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.ar.vtt 3.28 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.en.vtt 3.28 KB
Part 13-Module 01-Lesson 07_Narrative Structures/04. The New Journalism-ub1_Gwc6wN8.zh-CN.vtt 3.28 KB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.en.vtt 3.28 KB
Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.en.vtt 3.28 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.en.vtt 3.28 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.ar.vtt 3.28 KB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.pt-BR.vtt 3.28 KB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.ar.vtt 3.28 KB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.ar.vtt 3.28 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.en.vtt 3.28 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.ja.vtt 3.28 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.pt-BR.vtt 3.28 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.pt-BR.vtt 3.28 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.en-US.vtt 3.28 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.pt-BR.vtt 3.27 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/26. Updates-mpMHJQalRck.en.vtt 3.27 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.en.vtt 3.27 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.pt-BR.vtt 3.27 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.pt-BR.vtt 3.27 KB
Part 11-Module 01-Lesson 14_Validation/09. K-Fold CV in sklearn-QSYMwFbE7PA.zh-CN.vtt 3.27 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-c-v-Xa_R4SA.zh-CN.vtt 3.27 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.pt-BR.vtt 3.27 KB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.pt-BR.vtt 3.27 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.pt-BR.vtt 3.27 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.ar.vtt 3.27 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.pt-BR.vtt 3.27 KB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.ar.vtt 3.27 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.ar.vtt 3.27 KB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.ar.vtt 3.27 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt 3.26 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt 3.26 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/03. Resume Structure-POM0MqLTj98.zh-CN.vtt 3.26 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.en.vtt 3.26 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.en.vtt 3.26 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.ar.vtt 3.26 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.pt-BR.vtt 3.26 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.pt-BR.vtt 3.26 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.pt-BR.vtt 3.26 KB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.pt-BR.vtt 3.26 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.pt-BR.vtt 3.26 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-MlE3BuOvWnU.zh-CN.vtt 3.26 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/06. Appending And NumPy-fdpKvovBMe4.zh-CN.vtt 3.26 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-MlE3BuOvWnU.zh-CN.vtt 3.26 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.en.vtt 3.25 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.en.vtt 3.25 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.en.vtt 3.25 KB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.en-US.vtt 3.25 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.en.vtt 3.25 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt 3.25 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.pt-BR.vtt 3.25 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.en.vtt 3.25 KB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.en.vtt 3.25 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.ar.vtt 3.25 KB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.ar.vtt 3.25 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/31. Data Join with a Key Function-ue_TULswM1Y.en.vtt 3.25 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.th.vtt 3.25 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.en.vtt 3.24 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.en.vtt 3.24 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.en.vtt 3.24 KB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.pt-BR.vtt 3.24 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.en.vtt 3.24 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.ar.vtt 3.24 KB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.ar.vtt 3.24 KB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.ar.vtt 3.24 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.en.vtt 3.24 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-qsWz7r8muII.zh-CN.vtt 3.24 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -l1pZZKsESAc.zh-CN.vtt 3.24 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.pt-BR.vtt 3.24 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.en.vtt 3.23 KB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-6MdZ5NUfen0.en.vtt 3.23 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.ar.vtt 3.23 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.ar.vtt 3.23 KB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces) 2-tobH58uO24U.zh-CN.vtt 3.23 KB
Part 04-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.pt-BR.vtt 3.23 KB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.pt-BR.vtt 3.23 KB
Part 16-Module 01-Lesson 01_Anaconda/01. Why Anaconda-VXukXZv7SCQ.pt-BR.vtt 3.23 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.ar.vtt 3.23 KB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.pt-BR.vtt 3.23 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.ar.vtt 3.23 KB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.en.vtt 3.23 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.pt-BR.vtt 3.23 KB
Part 13-Module 01-Lesson 04_Design Principles/07. Small Multiples-HS_dsOQfwz8.zh-CN.vtt 3.22 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values-l3ergsxocok.en.vtt 3.22 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.pt-BR.vtt 3.22 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values-l3ergsxocok.en.vtt 3.22 KB
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-wPI9WOfpZbM.en.vtt 3.22 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt 3.22 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.en.vtt 3.22 KB
Part 19-Module 01-Lesson 02_Design/03. Exploratory vs. Explanatory Analysis-wvgBSMks4p8.zh-CN.vtt 3.22 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-fnbLMcd0FGQ.en.vtt 3.22 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.ar.vtt 3.22 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/05. Writing the Body-aK9Qnv3a6Wg.es-MX.vtt 3.22 KB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.en.vtt 3.21 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-6pGDwrJHitw.zh-CN.vtt 3.21 KB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.zh-CN.vtt 3.21 KB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.ja.vtt 3.21 KB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.ar.vtt 3.21 KB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.pt-BR.vtt 3.21 KB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.en.vtt 3.21 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.pt-BR.vtt 3.21 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.en.vtt 3.21 KB
Part 13-Module 01-Lesson 04_Design Principles/19. Pre-attentive Attributes-6UvLbIX0NQ4.en.vtt 3.21 KB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.ar.vtt 3.21 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-YbVuN2KOlt4.zh-CN.vtt 3.21 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/09. Investigating the Data-zJ_wWRTQUTs.pt-BR.vtt 3.2 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.es-MX.vtt 3.2 KB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.ar.vtt 3.2 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.ar.vtt 3.2 KB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.en-US.vtt 3.2 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.pt-BR.vtt 3.2 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/02. Intro to XML-eIVifBVJQIw.zh-CN.vtt 3.2 KB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.en.vtt 3.2 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.pt-BR.vtt 3.2 KB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.ar.vtt 3.2 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.ar.vtt 3.2 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.ar.vtt 3.2 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/01. Why Network-exjEm9Paszk.pt-BR.vtt 3.2 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.pt-BR.vtt 3.2 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.pt-BR.vtt 3.2 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.en.vtt 3.19 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.pt-BR.vtt 3.19 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.en.vtt 3.19 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.pt-BR.vtt 3.19 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/18. Joining Subqueries-rxy-fE5GeLY.pt-BR.vtt 3.19 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.pt-BR.vtt 3.19 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-9JfaMZcSlQA.zh-CN.vtt 3.19 KB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.en.vtt 3.19 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.ar.vtt 3.19 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.en.vtt 3.19 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.pt-BR.vtt 3.18 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/09. Reviewing our Street Name Audit-eIvm5rEMZGY.zh-CN.vtt 3.18 KB
Part 18-Module 04-Lesson 01_Cleaning Data/11. Cleaning For Tidiness -6nMKFhpVCRU.en.vtt 3.18 KB
Part 13-Module 01-Lesson 07_Narrative Structures/19. Viewer-driven Examples-ft07qc8rTwM.en.vtt 3.18 KB
Part 17-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.zh-CN.vtt 3.18 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.pt-BR.vtt 3.18 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.pt-BR.vtt 3.18 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/19. Plotting for DataFrames-CDVgPA0Mv2o.zh-CN.vtt 3.18 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/19. Plotting for DataFrames-CDVgPA0Mv2o.zh-CN.vtt 3.18 KB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.en.vtt 3.17 KB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.ar.vtt 3.17 KB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.en.vtt 3.17 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/05. Introduction to D3-mP1P0ybdZqI.zh-CN.vtt 3.17 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.ar.vtt 3.17 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.pt-BR.vtt 3.17 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.en.vtt 3.17 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.en.vtt 3.17 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.en.vtt 3.17 KB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.pt-BR.vtt 3.17 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.en-US.vtt 3.17 KB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.en.vtt 3.17 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.en-US.vtt 3.17 KB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.pt-BR.vtt 3.17 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/13. Where's the Data-rHQ8z4fIthA.pt-BR.vtt 3.17 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.en.vtt 3.17 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.ar.vtt 3.17 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.ar.vtt 3.16 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.en.vtt 3.16 KB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.en.vtt 3.16 KB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.en-US.vtt 3.16 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.pt-BR.vtt 3.16 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.ar.vtt 3.16 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.pt-BR.vtt 3.16 KB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.en.vtt 3.16 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.en.vtt 3.16 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/20. Plotting With Pandas-kR7KZFqciFE.zh-CN.vtt 3.16 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.en.vtt 3.16 KB
Part 12-Module 02-Lesson 06_Graphs/10. DFS-BC8jEidd2EQ.pt-BR.vtt 3.16 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/04. Statistical Significance-kpdwHL54eys.zh-CN.vtt 3.16 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/08. Overview of Business Example-tlSe7H9BDy8.zh-CN.vtt 3.15 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/18. How to Decrease Experiment Size-4-MF0UZac8o.zh-CN.vtt 3.15 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.pt-BR.vtt 3.15 KB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.ar.vtt 3.15 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.pt-BR.vtt 3.15 KB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.pt-BR.vtt 3.15 KB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.ar.vtt 3.15 KB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.ar.vtt 3.15 KB
Part 13-Module 01-Lesson 07_Narrative Structures/24. Annotations World Cup Attendance Chart-Aq39o9xrW5A.zh-CN.vtt 3.15 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.zh-CN.vtt 3.15 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-UFcCmB7Xvvs.zh-CN.vtt 3.15 KB
Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.en.vtt 3.15 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.en.vtt 3.14 KB
Part 13-Module 01-Lesson 07_Narrative Structures/13. Errors in Data Collection-xcYDjXpYbs0.zh-CN.vtt 3.14 KB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.pt-BR.vtt 3.14 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.pt-BR.vtt 3.14 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.pt-BR.vtt 3.14 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.pt-BR.vtt 3.14 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.ja.vtt 3.14 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.pt-BR.vtt 3.14 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.pt-BR.vtt 3.14 KB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.ar.vtt 3.13 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.ar.vtt 3.13 KB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.pt-BR.vtt 3.13 KB
Part 09-Module 01-Lesson 03_Explore One Variable/03. Pseudo-Facebook User Data-8FD_iOP24UA.ja.vtt 3.13 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.zh-CN.vtt 3.13 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/09. Debugging-Bz1tlvkql9Q.zh-CN.vtt 3.13 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.ar.vtt 3.13 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.en.vtt 3.13 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.en.vtt 3.13 KB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.en.vtt 3.13 KB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.ja.vtt 3.12 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.en.vtt 3.12 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.ar.vtt 3.12 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.pt-BR.vtt 3.12 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/23. Nonparametric Answers-Z0QcZHrflmc.zh-CN.vtt 3.12 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.ar.vtt 3.12 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.en.vtt 3.12 KB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.pt-BR.vtt 3.12 KB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.pt-BR.vtt 3.12 KB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.en.vtt 3.12 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/04. Assessing the Quality of Data Pt. 2-8onBHqvvrig.zh-CN.vtt 3.12 KB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.pt-BR.vtt 3.12 KB
Part 12-Module 02-Lesson 05_Trees/15. Heaps-M3B0UJWS_ag.pt-BR.vtt 3.12 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.pt-BR.vtt 3.12 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.pt-BR.vtt 3.12 KB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.pt-BR.vtt 3.12 KB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.en.vtt 3.12 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.ar.vtt 3.11 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.en.vtt 3.11 KB
Part 19-Module 01-Lesson 02_Design/05. What Makes a Bad Visual-zbvB_9f7bFs.zh-CN.vtt 3.11 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.ar.vtt 3.11 KB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.en.vtt 3.11 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.en.vtt 3.11 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.pt-BR.vtt 3.11 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/07. Efficiency-I-RASDPbDrI.zh-CN.vtt 3.11 KB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.ar.vtt 3.11 KB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.pt-BR.vtt 3.11 KB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.en.vtt 3.11 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/13. Metric Definition Example-1EoJTK_S0mk.zh-CN.vtt 3.11 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.ar.vtt 3.11 KB
Part 13-Module 01-Lesson 04_Design Principles/51. D3 Functions-4OkB_Ybo0i0.zh-CN.vtt 3.11 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/20. Clean Define-qHB4jsqcfi4.zh-CN.vtt 3.11 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.pt-BR.vtt 3.11 KB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.pt-BR.vtt 3.1 KB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.ar.vtt 3.1 KB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.ar.vtt 3.1 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.en.vtt 3.1 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.en.vtt 3.1 KB
Part 13-Module 01-Lesson 07_Narrative Structures/62. Adding Circles to the Legend-FlbCPYGCKqk.zh-CN.vtt 3.1 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.pt-BR.vtt 3.1 KB
Part 21-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.zh-CN.vtt 3.1 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.en.vtt 3.1 KB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.ar.vtt 3.1 KB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.pt-BR.vtt 3.1 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.en.vtt 3.09 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.pt-BR.vtt 3.09 KB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-jkJ4dbbpVCQ.zh-CN.vtt 3.09 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/13. Population vs. Cohort-HC2dunMuVW4.en.vtt 3.09 KB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.en.vtt 3.09 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/02. Data Modeling in MongoDB-6sDkIE_nAGI.zh-CN.vtt 3.09 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/23. Making Histograms-0J5lNTGbspg.zh-CN.vtt 3.09 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.en.vtt 3.08 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.ar.vtt 3.08 KB
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-vLlj5nNj8x4.pt-BR.vtt 3.08 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.en.vtt 3.08 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.ar.vtt 3.08 KB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.pt-BR.vtt 3.08 KB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.ar.vtt 3.08 KB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.ar.vtt 3.08 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.es.vtt 3.08 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.es.vtt 3.08 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.zh-CN.vtt 3.08 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-UlRN0J1lYtg.zh-CN.vtt 3.08 KB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.ar.vtt 3.08 KB
Part 16-Module 03-Lesson 01_Basic SQL/11. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt 3.08 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. SELECT FROM Statements-urOYuuav4BY.zh-CN.vtt 3.08 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.zh-CN.vtt 3.08 KB
Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.es-MX.vtt 3.08 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.ar.vtt 3.08 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.en.vtt 3.08 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.ar.vtt 3.08 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-4RmQYWI8lY4.zh-CN.vtt 3.08 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.pt-BR.vtt 3.08 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.ar.vtt 3.08 KB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.ja.vtt 3.08 KB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.ar.vtt 3.08 KB
Part 16-Module 03-Lesson 02_SQL Joins/18. JOINs and Filtering-aI1kbDDNs4w.pt-BR.vtt 3.08 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.en.vtt 3.08 KB
Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.en.vtt 3.08 KB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.en.vtt 3.08 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.en.vtt 3.07 KB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.ar.vtt 3.07 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.ar.vtt 3.07 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.zh-CN.vtt 3.07 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.ar.vtt 3.07 KB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.pt-BR.vtt 3.07 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.pt-BR.vtt 3.07 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.pt-BR.vtt 3.07 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/12. Gathering Data-JsVg95-amjI.zh-CN.vtt 3.07 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.en.vtt 3.07 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.ja.vtt 3.07 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/03. Dijkstra's Algorithm-SoPMK03cOgk.zh-CN.vtt 3.07 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.pt-BR.vtt 3.07 KB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.ar.vtt 3.07 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.ar.vtt 3.07 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.en.vtt 3.07 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.en.vtt 3.07 KB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.zh-CN.vtt 3.07 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.pt-BR.vtt 3.07 KB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.ar.vtt 3.07 KB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.en.vtt 3.07 KB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.ar.vtt 3.07 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.ar.vtt 3.06 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.pt-BR.vtt 3.06 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.ar.vtt 3.06 KB
Part 19-Module 01-Lesson 02_Design/15. Shape, Size, and other Tools-fzEliHW3ZLM.zh-CN.vtt 3.06 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt 3.06 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.ar.vtt 3.06 KB
Part 18-Module 03-Lesson 01_Assessing Data/17. Tidiness Visual Assessment Solution-H50mPHHp6fY.pt-BR.vtt 3.06 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.en.vtt 3.06 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.zh-CN.vtt 3.06 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.pt-BR.vtt 3.06 KB
Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.en.vtt 3.06 KB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.ar.vtt 3.05 KB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.ar.vtt 3.05 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.pt-BR.vtt 3.05 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.en.vtt 3.05 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.zh-CN.vtt 3.05 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.ar.vtt 3.05 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-XsyavvSGjLM.zh-CN.vtt 3.05 KB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -exMGBx6Rs_E.en.vtt 3.05 KB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.pt-BR.vtt 3.05 KB
Part 12-Module 02-Lesson 06_Graphs/13. Eulerian Path-zS34kHSo7fs.zh-CN.vtt 3.05 KB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.en.vtt 3.05 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.ar.vtt 3.05 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.en.vtt 3.04 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.en.vtt 3.04 KB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.en.vtt 3.04 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-YW-uud_btQ8.zh-CN.vtt 3.04 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.ar.vtt 3.04 KB
Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.pt-BR.vtt 3.04 KB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.pt-BR.vtt 3.04 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.en.vtt 3.04 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.ar.vtt 3.04 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.en.vtt 3.04 KB
Part 18-Module 03-Lesson 01_Assessing Data/07. Visual Assessment -GVVibuIg3Ro.zh-CN.vtt 3.04 KB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.ar.vtt 3.04 KB
Part 06-Module 01-Lesson 03_Analyzing Data/02. Twitter Data Set-xiqleK_px_Q.zh-CN.vtt 3.04 KB
Part 11-Module 01-Lesson 09_Clustering/10. K-Means Clustering Visualization 2-fQXXa-CAoS0.zh-CN.vtt 3.04 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/08. Efficiency of Bubble Sort-KddkHygi7is.zh-CN.vtt 3.04 KB
Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.en.vtt 3.04 KB
Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.en.vtt 3.04 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/06. Dynamic Programming-VQeFcG9pjJU.zh-CN.vtt 3.04 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.ar.vtt 3.04 KB
Part 14-Module 01-Lesson 05_Analyzing Results/11. Gotchas Simpson’s Paradox-GSPTcqNpab8.zh-CN.vtt 3.03 KB
Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.en.vtt 3.03 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.ar.vtt 3.03 KB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.en.vtt 3.03 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.en.vtt 3.03 KB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.pt-BR.vtt 3.03 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.en.vtt 3.03 KB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.pt-BR.vtt 3.03 KB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.pt-BR.vtt 3.03 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.ar.vtt 3.03 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.pt-BR.vtt 3.03 KB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.ar.vtt 3.03 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.en-US.vtt 3.03 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.pt-BR.vtt 3.03 KB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.ar.vtt 3.03 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.en.vtt 3.03 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.ar.vtt 3.02 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.en.vtt 3.02 KB
Part 18-Module 02-Lesson 01_Gathering Data/13. Text File Structure-O4qEWpXZLQg.zh-CN.vtt 3.02 KB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.en.vtt 3.02 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.pt-BR.vtt 3.02 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.pt-BR.vtt 3.02 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.pt-BR.vtt 3.02 KB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.en.vtt 3.02 KB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.pt-BR.vtt 3.02 KB
Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.ar.vtt 3.02 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.pt-BR.vtt 3.02 KB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.ar.vtt 3.02 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.it.vtt 3.02 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.pt-BR.vtt 3.02 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/05. Hashing-kCPFfHx_LgQ.zh-CN.vtt 3.02 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.en.vtt 3.01 KB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.pt-BR.vtt 3.01 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.es.vtt 3.01 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.es.vtt 3.01 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/32. Binding Data-yW9LEMFOzgY.zh-CN.vtt 3.01 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.ar.vtt 3.01 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.en.vtt 3.01 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.en.vtt 3.01 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.ar.vtt 3.01 KB
Part 17-Module 01-Lesson 08_Python Probability Practice/04. Simulating Many Coin Flips-AqpWQIj2V5Y.zh-CN.vtt 3.01 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-fRNDqy-le8U.zh-CN.vtt 3.01 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.ja.vtt 3.01 KB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.ar.vtt 3.01 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.en.vtt 3.01 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.en.vtt 3 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.en.vtt 3 KB
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Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.en.vtt 2.91 KB
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Part 12-Module 01-Lesson 03_Interview Fails/03. Interviewing Fails Siya Raj Purohit-wYop-N5YgeA.zh-CN.vtt 2.9 KB
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.pt-BR.vtt 2.87 KB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.en.vtt 2.87 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/03. Good Data Visualization-ePekYbKs60U.zh-CN.vtt 2.87 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.pt-BR.vtt 2.87 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.pt-BR.vtt 2.87 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.it.vtt 2.87 KB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.pt-BR.vtt 2.87 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.ar.vtt 2.87 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt 2.87 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.en.vtt 2.87 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. Performance Tuning 1-5mVfYZ_bfRo.zh-CN.vtt 2.87 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.en.vtt 2.87 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.en.vtt 2.87 KB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.pt-BR.vtt 2.87 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.en.vtt 2.87 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.pt-BR.vtt 2.87 KB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.ar.vtt 2.86 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.en.vtt 2.86 KB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.ja.vtt 2.86 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-j5tA__Dq-sQ.ar.vtt 2.86 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/20. Calculating the p-value-_W3Jg7jQ8jI.zh-CN.vtt 2.86 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/08. Declaring Relationships-1FjqstT1faI.zh-CN.vtt 2.86 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.ja.vtt 2.86 KB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.ar.vtt 2.86 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.en.vtt 2.86 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.en.vtt 2.86 KB
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-x-8-2zy8gmI.zh-CN.vtt 2.86 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.en.vtt 2.86 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.pt-BR.vtt 2.86 KB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.en-US.vtt 2.86 KB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.pt-BR.vtt 2.86 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.pt-BR.vtt 2.86 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -CSW2i2jIqyA.zh-CN.vtt 2.86 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.en.vtt 2.86 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.ar.vtt 2.86 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.ar.vtt 2.86 KB
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.ja.vtt 2.86 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.ja.vtt 2.86 KB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.en.vtt 2.86 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/14. Helpful Symbols-w4_8YCp-9fI.zh-CN.vtt 2.85 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.pt-BR.vtt 2.85 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/09. String Keys-WyFwieF1NN4.zh-CN.vtt 2.85 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.en.vtt 2.85 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.en.vtt 2.85 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-9L9bhMCHQ-M.zh-CN.vtt 2.85 KB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.pt-BR.vtt 2.85 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.pt-BR.vtt 2.85 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.ar.vtt 2.85 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.pt-BR.vtt 2.85 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/14. Loading Data with Nested Functions-ME6F4Nyjv8o.zh-CN.vtt 2.85 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/14. Procedure-6rSJRr9OtHM.zh-CN.vtt 2.85 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.pt-BR.vtt 2.85 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.en.vtt 2.85 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.pt-BR.vtt 2.84 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-in2hLEl_eJU.zh-CN.vtt 2.84 KB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.en.vtt 2.84 KB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.ar.vtt 2.84 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.th.vtt 2.84 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.pt-BR.vtt 2.84 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.en.vtt 2.84 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/10. Details of the Data Science Process-8TeiMKUmoYQ.zh-CN.vtt 2.84 KB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.ja.vtt 2.84 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.es-ES.vtt 2.84 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.ar.vtt 2.84 KB
Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.pt-BR.vtt 2.84 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.en.vtt 2.84 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.en.vtt 2.83 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-xsdj1qJwgk4.zh-CN.vtt 2.83 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.ar.vtt 2.83 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/13. GROUP BY-9vb67TF4WV0.zh-CN.vtt 2.83 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.pt-BR.vtt 2.83 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.pt-BR.vtt 2.83 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.en.vtt 2.83 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/17. Aggregations-4nGL3y3Nq-0.zh-CN.vtt 2.83 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/03. Get to Know the PDF-52HAbu6_u9I.zh-CN.vtt 2.83 KB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.en.vtt 2.83 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.pt-BR.vtt 2.83 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.en.vtt 2.83 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.en.vtt 2.83 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-Q2M8xyY47fc.zh-CN.vtt 2.83 KB
Part 12-Module 02-Lesson 05_Trees/09. Insert-j6PkPa2ZHWg.zh-CN.vtt 2.83 KB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.pt-BR.vtt 2.82 KB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.pt-BR.vtt 2.82 KB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.en.vtt 2.82 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.en.vtt 2.82 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.pt-BR.vtt 2.82 KB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.zh-CN.vtt 2.82 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt 2.82 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt 2.82 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.pt-BR.vtt 2.82 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.en.vtt 2.82 KB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.ar.vtt 2.82 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.ar.vtt 2.82 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.ar.vtt 2.82 KB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.ar.vtt 2.82 KB
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 Solution-kqcuw1qCLEM.zh-CN.vtt 2.82 KB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.pt-BR.vtt 2.82 KB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.pt-BR.vtt 2.82 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.ar.vtt 2.81 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/16. Assess Programmatic-6JubHCD7dh4.zh-CN.vtt 2.81 KB
Part 05-Module 01-Lesson 05_Data Quality/17. Consistency-_5AnMdslWg4.zh-CN.vtt 2.81 KB
Part 12-Module 02-Lesson 02_List-Based Collections/11. Queues-XAbzlilAHZw.zh-CN.vtt 2.81 KB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.ar.vtt 2.81 KB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.pt-BR.vtt 2.81 KB
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-paj5z9U1OBk.zh-CN.vtt 2.81 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-TjY0Q66Yh-s.zh-CN.vtt 2.81 KB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.en.vtt 2.81 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.pt-BR.vtt 2.81 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.en.vtt 2.81 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.pt-BR.vtt 2.81 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.en.vtt 2.81 KB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.ar.vtt 2.81 KB
Part 21-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.zh-CN.vtt 2.81 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.en.vtt 2.8 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.ar.vtt 2.8 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.ar.vtt 2.8 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.ar.vtt 2.8 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.ar.vtt 2.8 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.ar.vtt 2.8 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.ja.vtt 2.8 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/06. CSV Format-ra93hy88cok.zh-CN.vtt 2.8 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.en-US.vtt 2.8 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.pt-BR.vtt 2.8 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.pt-BR.vtt 2.8 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.pt-BR.vtt 2.8 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.pt-BR.vtt 2.8 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.pt-BR.vtt 2.8 KB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.en.vtt 2.79 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.en.vtt 2.79 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.ar.vtt 2.79 KB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.pt-BR.vtt 2.79 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.pt-BR.vtt 2.79 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.pt-BR.vtt 2.79 KB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.en.vtt 2.79 KB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.pt-BR.vtt 2.79 KB
Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.en.vtt 2.79 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.zh-CN.vtt 2.79 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.zh-CN.vtt 2.79 KB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.pt-BR.vtt 2.79 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/06. Accessing Elements of a DataFrame-hZp9cVuiPo0.zh-CN.vtt 2.79 KB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.en.vtt 2.79 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/16. Type And Quality Plot - Part 1-iRCS1sE78KI.zh-CN.vtt 2.79 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/08. Unit of Analysis vs. Unit of Diversion-rzim0wu_0kM.zh-CN.vtt 2.79 KB
Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.pt-BR.vtt 2.79 KB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.ar.vtt 2.79 KB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.en.vtt 2.78 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-gfuknvEP2ro.zh-CN.vtt 2.78 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.pt-BR.vtt 2.78 KB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.en.vtt 2.78 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.pt-BR.vtt 2.78 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.en.vtt 2.78 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.ar.vtt 2.78 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.pt-BR.vtt 2.78 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.ar.vtt 2.78 KB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.ar.vtt 2.78 KB
Part 13-Module 01-Lesson 07_Narrative Structures/53. Inspecting Accessor Functions-bRkkMdkkFQw.zh-CN.vtt 2.78 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/09. 06 Practice With Marks And Filters-RPAv7WLkutk.en.vtt 2.78 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.ar.vtt 2.78 KB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.en.vtt 2.77 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-joTa_FeMZ2s.zh-CN.vtt 2.77 KB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.ar.vtt 2.77 KB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.ar.vtt 2.77 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.ar.vtt 2.77 KB
Part 18-Module 04-Lesson 01_Cleaning Data/08. Addressing Missing Data First -ArAGZCUMj9Q.en.vtt 2.77 KB
Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.pt-BR.vtt 2.77 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.en.vtt 2.77 KB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.ar.vtt 2.77 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.en.vtt 2.77 KB
Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.en.vtt 2.77 KB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.pt-BR.vtt 2.77 KB
Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.pt-BR.vtt 2.77 KB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.pt-BR.vtt 2.77 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.ar.vtt 2.77 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.pt-BR.vtt 2.77 KB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.en.vtt 2.77 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.en.vtt 2.77 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -Y288CGrwGy4.zh-CN.vtt 2.76 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.zh-CN.vtt 2.76 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.en-US.vtt 2.76 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.pt-BR.vtt 2.76 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.en.vtt 2.76 KB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.ar.vtt 2.76 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.pt-BR.vtt 2.76 KB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.pt-BR.vtt 2.76 KB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.pt-BR.vtt 2.76 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt 2.76 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Do Analysts Like SQL-uCNOtUht2Xc.zh-CN.vtt 2.76 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.ar.vtt 2.76 KB
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Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.en.vtt 2.76 KB
Part 13-Module 01-Lesson 05_Dimple.js/20. Object Oriented Design and Charts-2uzNpGWdavc.zh-CN.vtt 2.75 KB
Part 13-Module 01-Lesson 07_Narrative Structures/17. Different Types of Narrative Structures-vTlpDo33ezg.zh-CN.vtt 2.75 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.ar.vtt 2.75 KB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.pt-BR.vtt 2.75 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.en.vtt 2.75 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.ar.vtt 2.75 KB
Part 11-Module 01-Lesson 12_Feature Selection/15. Regularization-l9V5tlIWTvs.zh-CN.vtt 2.75 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/02. Defining Data Visualization-TMH43G11OnQ.zh-CN.vtt 2.75 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/12. Pandas Series-V7zAB9dUaFY.zh-CN.vtt 2.75 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.en-US.vtt 2.75 KB
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Part 02-Module 01-Lesson 01_Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.zh-CN.vtt 2.75 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/04. Define Constructs-J2kY_Xf7i1E.zh-CN.vtt 2.75 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.en.vtt 2.75 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-4QIEdzv6g6w.pt-BR.vtt 2.75 KB
Part 09-Module 01-Lesson 03_Explore One Variable/27. Box Plots, Quartiles, and Friendships-ykFuZOPCU88.zh-CN.vtt 2.75 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.en.vtt 2.75 KB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.hi.vtt 2.75 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.en.vtt 2.75 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.en.vtt 2.75 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.en.vtt 2.75 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.ja.vtt 2.75 KB
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/27. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt 2.74 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/02. Descriptive vs. Inferential Statistics-XV9pd8-RZ78.zh-CN.vtt 2.74 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.es-MX.vtt 2.74 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.ja.vtt 2.74 KB
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt 2.74 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.es-MX.vtt 2.74 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/10. Inspect GeoJSON-ThA4r4nzyj4.zh-CN.vtt 2.74 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.en.vtt 2.74 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.pt-BR.vtt 2.74 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.ja.vtt 2.74 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.ja.vtt 2.74 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.en.vtt 2.74 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.ar.vtt 2.74 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.en.vtt 2.74 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/06. Intro to Sorting-Z6yuIen71zM.zh-CN.vtt 2.74 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.pt-BR.vtt 2.74 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/08. Calculating Correlation-yLql7kR_6GE.zh-CN.vtt 2.73 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.ar.vtt 2.73 KB
Part 21-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.zh-CN.vtt 2.73 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/08. Calculating Correlation-yLql7kR_6GE.zh-CN.vtt 2.73 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.pt-BR.vtt 2.73 KB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.hi.vtt 2.73 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.ja.vtt 2.73 KB
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Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.th.vtt 2.73 KB
Part 11-Module 01-Lesson 13_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.zh-CN.vtt 2.73 KB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.en.vtt 2.73 KB
Part 13-Module 01-Lesson 07_Narrative Structures/41. Parsing Data Before the Draw Function-WALbqgiDHNI.zh-CN.vtt 2.73 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.en.vtt 2.73 KB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.pt-BR.vtt 2.73 KB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.ar.vtt 2.73 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.ar.vtt 2.73 KB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.en.vtt 2.73 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.en.vtt 2.72 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/30. Code Structure and JavaScript-vPCDvEOjP7c.zh-CN.vtt 2.72 KB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.ar.vtt 2.72 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/05. Intro to CSVs-UFiJYYPL95g.zh-CN.vtt 2.72 KB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.ja.vtt 2.72 KB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.ar.vtt 2.72 KB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.en.vtt 2.72 KB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.ar.vtt 2.72 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.pt-BR.vtt 2.72 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-TeFF9wXiFfs.zh-CN.vtt 2.72 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/12. Drawing and Altering the Map-soflPyVhb6o.zh-CN.vtt 2.72 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/01. Course Introduction-NKBUbUiedzc.zh-CN.vtt 2.72 KB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.en.vtt 2.72 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.ar.vtt 2.72 KB
Part 13-Module 01-Lesson 07_Narrative Structures/21. Drone Strikes and Gun Deaths-_MXW29cfh_8.zh-CN.vtt 2.72 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.ar.vtt 2.72 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/07. Parsing CSV Files-hmhlyOVAVOs.zh-CN.vtt 2.72 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.pt-BR.vtt 2.71 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-lNYLU1b4qoM.zh-CN.vtt 2.71 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.es-MX.vtt 2.71 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/20. Absolute or Relative Difference-TNcT_v2g3OQ.zh-CN.vtt 2.71 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.pt-BR.vtt 2.71 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.en-US.vtt 2.71 KB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.pt-BR.vtt 2.71 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.en.vtt 2.71 KB
Part 13-Module 01-Lesson 07_Narrative Structures/61. I am Legend-EdiM9XCqc0Y.zh-CN.vtt 2.71 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/02. Problems Solved by Data Analysts-jZEbCVZzwUk.zh-CN.vtt 2.71 KB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.pt-BR.vtt 2.71 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/48. Matt's Tips for Making Maps-HCYCT2TXhAM.zh-CN.vtt 2.71 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.pt-BR.vtt 2.71 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.ar.vtt 2.71 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.ar.vtt 2.71 KB
Part 05-Module 02-Lesson 01_Data and Tables/10. How Queries Happen-v3EkXogyIL4.zh-CN.vtt 2.71 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.ar.vtt 2.71 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.en.vtt 2.71 KB
Part 17-Module 01-Lesson 16_Logistic Regression/04. Fitting Logistic Regression In Python-baQf-XiZQQ4.zh-CN.vtt 2.71 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.ar.vtt 2.71 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.ar.vtt 2.7 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.zh-CN.vtt 2.7 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/01. What is Tableau-LeCpU8HvVg8.zh-CN.vtt 2.7 KB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.en.vtt 2.7 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.zh-CN.vtt 2.7 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/07. Use Your Elevator Pitch-e-v60ieggSs.pt-BR.vtt 2.7 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.pt-BR.vtt 2.7 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/03. Two-Dimensional NumPy Arrays-dutQvWMO0AU.zh-CN.vtt 2.7 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.en.vtt 2.7 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.en.vtt 2.7 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.zh-CN.vtt 2.7 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.zh-CN.vtt 2.7 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.en.vtt 2.7 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.en.vtt 2.7 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.pt-BR.vtt 2.7 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.pt-BR.vtt 2.7 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.pt-BR.vtt 2.7 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/03. The Benefits of Interactivity-fIIyFYQyGLk.zh-CN.vtt 2.7 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.ar.vtt 2.7 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/03. Iterative Parsing-pxUvIP4PQt0.zh-CN.vtt 2.7 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/03. Iterative Parsing-pxUvIP4PQt0.zh-CN.vtt 2.7 KB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.pt-BR.vtt 2.7 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.en.vtt 2.69 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.pt-BR.vtt 2.69 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.en-US.vtt 2.69 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.ar.vtt 2.69 KB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.ar.vtt 2.69 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.pt-BR.vtt 2.69 KB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.pt-BR.vtt 2.69 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.pt-BR.vtt 2.69 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.en.vtt 2.69 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/23. Marks And Filters-FeYRmZHHu0A.zh-CN.vtt 2.69 KB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.ar.vtt 2.69 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.pt-BR.vtt 2.69 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.en.vtt 2.69 KB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.pt-BR.vtt 2.68 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.en.vtt 2.68 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt 2.68 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.pt-BR.vtt 2.68 KB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.pt-BR.vtt 2.68 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.ar.vtt 2.68 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.en.vtt 2.68 KB
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-HEnJRwJ23us.zh-CN.vtt 2.68 KB
Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.pt-BR.vtt 2.68 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.pt-BR.vtt 2.68 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.pt-BR.vtt 2.68 KB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.en.vtt 2.68 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.en.vtt 2.68 KB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.en-US.vtt 2.68 KB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.es-ES.vtt 2.68 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/23. McDonald's-29Vf6PytVbA.zh-CN.vtt 2.68 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/23. McDonald's-29Vf6PytVbA.zh-CN.vtt 2.68 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-iJEBxsKDDoE.zh-CN.vtt 2.68 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.en.vtt 2.68 KB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.ar.vtt 2.68 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/15. More on Performance Tuning-ZK1FvNH10Ag.zh-CN.vtt 2.68 KB
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-DxCwtkrYR-s.zh-CN.vtt 2.68 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-N6wKbV1DVos.zh-CN.vtt 2.67 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.ar.vtt 2.67 KB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.en.vtt 2.67 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/16. Performance Tuning 2-arMtEhSoq7E.ar.vtt 2.67 KB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.pt-BR.vtt 2.67 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.ar.vtt 2.67 KB
Part 11-Module 01-Lesson 09_Clustering/01. Unsupervised Learning-Mx9f99bRB3Q.zh-CN.vtt 2.67 KB
Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.en.vtt 2.67 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.en.vtt 2.67 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.ja.vtt 2.67 KB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.ar.vtt 2.67 KB
Part 05-Module 01-Lesson 05_Data Quality/19. More About Correcting Data-vWBMgSQvsVk.zh-CN.vtt 2.67 KB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.en.vtt 2.67 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.pt-BR.vtt 2.67 KB
Part 03-Module 01-Lesson 20_L8 Estimation/06. Interval Estimate for Population Mean-ECRw3cSiy6o.zh-CN.vtt 2.66 KB
Part 11-Module 01-Lesson 02_Naive Bayes/36. Naive Bayes Strengths and Weaknesses-nfbKTrufPOs.zh-CN.vtt 2.66 KB
Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.ar.vtt 2.66 KB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.pt-BR.vtt 2.66 KB
Part 09-Module 01-Lesson 02_R Basics/12. Factor Variables-0bkvt4KEqjE.zh-CN.vtt 2.66 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.pt-BR.vtt 2.66 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.pt-BR.vtt 2.66 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.en.vtt 2.66 KB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.ar.vtt 2.66 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/02. Cleaning with String Functions-y1fduSu7Ovc.zh-CN.vtt 2.66 KB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.pt-BR.vtt 2.66 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.pt-BR.vtt 2.66 KB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.pt-BR.vtt 2.66 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.en.vtt 2.66 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.en.vtt 2.66 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.en.vtt 2.66 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.en.vtt 2.66 KB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.pt-BR.vtt 2.66 KB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.pt-BR.vtt 2.65 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.ja.vtt 2.65 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.pt-BR.vtt 2.65 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.en.vtt 2.65 KB
Part 07-Module 01-Lesson 01_GitHub Review/02. GitHub profile important items-prvPVTjVkwQ.zh-CN.vtt 2.65 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.ar.vtt 2.65 KB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.en.vtt 2.65 KB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.en-US.vtt 2.65 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.en.vtt 2.65 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.pt-BR.vtt 2.65 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.en.vtt 2.65 KB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.pt-BR.vtt 2.65 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.en.vtt 2.65 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/04. ggplot Syntax-7XyFjPDPoZQ.zh-CN.vtt 2.65 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.ar.vtt 2.65 KB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.en.vtt 2.65 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.pt-BR.vtt 2.65 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.pt-BR.vtt 2.64 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.en.vtt 2.64 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.en.vtt 2.64 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.en.vtt 2.64 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.en.vtt 2.64 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.en.vtt 2.64 KB
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-20aUUbuzALM.zh-CN.vtt 2.64 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.en.vtt 2.64 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.pt-BR.vtt 2.64 KB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.en.vtt 2.64 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.zh-CN.vtt 2.64 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.zh-CN.vtt 2.64 KB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.pt-BR.vtt 2.64 KB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.ar.vtt 2.64 KB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.pt-BR.vtt 2.64 KB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.zh-CN.vtt 2.64 KB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.ja.vtt 2.63 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/04. Ways in the Open Street Map XML-1OwIbj9dcLo.zh-CN.vtt 2.63 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/05. Ways in the Open Street Map XML-1OwIbj9dcLo.zh-CN.vtt 2.63 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.ar.vtt 2.63 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.en.vtt 2.63 KB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.en.vtt 2.63 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.pt-BR.vtt 2.63 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.ar.vtt 2.63 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.pt-BR.vtt 2.63 KB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.ar.vtt 2.63 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.en.vtt 2.63 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.pt-BR.vtt 2.63 KB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.pt-BR.vtt 2.63 KB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.ar.vtt 2.63 KB
Part 11-Module 01-Lesson 11_Text Learning/10. Stemming to Consolidate Vocabulary-gBwGPI0srBE.zh-CN.vtt 2.63 KB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.en.vtt 2.63 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/19. Using Beautiful Soup-_rDjie-TaS8.zh-CN.vtt 2.63 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/04. Writing Your Introduction-5S5PH73WLLY.es-MX.vtt 2.63 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.ar.vtt 2.63 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/10. -v5CqqhgvG-U.zh-CN.vtt 2.63 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.en.vtt 2.63 KB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.pt-BR.vtt 2.63 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.en.vtt 2.63 KB
Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.ar.vtt 2.63 KB
Part 18-Module 03-Lesson 01_Assessing Data/06. Types vs. Steps -oZmndg-BnPk.zh-CN.vtt 2.63 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.pt-BR.vtt 2.63 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.zh-CN.vtt 2.63 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.en.vtt 2.62 KB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.pt-BR.vtt 2.62 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.ar.vtt 2.62 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.ar.vtt 2.62 KB
Part 17-Module 01-Lesson 14_Regression/13. Fitting A Regression Line-xQob80zrT3s.zh-CN.vtt 2.62 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.pt-BR.vtt 2.62 KB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.ar.vtt 2.62 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.pt-BR.vtt 2.62 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-PZSPhQCVABg.zh-CN.vtt 2.62 KB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.pt-BR.vtt 2.62 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/15. What About More Than Two Variables -ufKcdUbLj9c.zh-CN.vtt 2.62 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/15. Hypotheses-DepOzUJw_bQ.zh-CN.vtt 2.62 KB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.pt-BR.vtt 2.62 KB
Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.en.vtt 2.61 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.pt-BR.vtt 2.61 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.ar.vtt 2.61 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.en.vtt 2.61 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.ar.vtt 2.61 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/21. Variability-1KmFcGt6Uo0.zh-CN.vtt 2.61 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.ar.vtt 2.61 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.en.vtt 2.61 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/01. Get an Interview with a Cover Letter!-BH1KY63YfAM.zh-CN.vtt 2.61 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.pt-BR.vtt 2.61 KB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.pt-BR.vtt 2.61 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.en.vtt 2.61 KB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.ja.vtt 2.61 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.pt-BR.vtt 2.61 KB
Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.ar.vtt 2.61 KB
Part 09-Module 01-Lesson 01_What is EDA/05. Goals of EDA-NEvuulahg2g.zh-CN.vtt 2.61 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/17. 07 Calculated Fields-dXEvq03E5lc.zh-CN.vtt 2.6 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.ar.vtt 2.6 KB
Part 13-Module 01-Lesson 05_Dimple.js/34. Summary of Dimple and Chart Types-OrdADko3k1Q.zh-CN.vtt 2.6 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.ar.vtt 2.6 KB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.en.vtt 2.6 KB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-OurfO1ZR2GU.zh-CN.vtt 2.6 KB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.en.vtt 2.6 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.ar.vtt 2.6 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.en-US.vtt 2.6 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.ar.vtt 2.6 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.ar.vtt 2.6 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.pt-BR.vtt 2.6 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.ar.vtt 2.6 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.en.vtt 2.6 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.pt-BR.vtt 2.6 KB
Part 21-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.zh-CN.vtt 2.6 KB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.ar.vtt 2.6 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/08. Statistical vs. Practical Differences-RKHD1wzxxPA.zh-CN.vtt 2.6 KB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.en.vtt 2.6 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.pt-BR.vtt 2.6 KB
Part 13-Module 01-Lesson 07_Narrative Structures/03. Correlation vs Causation-8u96-UEf_ms.zh-CN.vtt 2.6 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.en-US.vtt 2.59 KB
Part 14-Module 01-Lesson 05_Analyzing Results/08. Single Metric Introduction-StP9L9f70EU.zh-CN.vtt 2.59 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.es-MX.vtt 2.59 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.ar.vtt 2.59 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.en.vtt 2.59 KB
Part 18-Module 03-Lesson 01_Assessing Data/04. Unclean Data Dirty Messy -WG6mil60jq0.en.vtt 2.59 KB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.en.vtt 2.59 KB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.ar.vtt 2.59 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-JqyUT7RbvgI.zh-CN.vtt 2.59 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/19. Sizing Triggering-ae9SWJxGM0w.zh-CN.vtt 2.59 KB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.ar.vtt 2.59 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.pt-BR.vtt 2.59 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.ar.vtt 2.59 KB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.en.vtt 2.58 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.zh-CN.vtt 2.58 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-6CiZB0N7y64.zh-CN.vtt 2.58 KB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.en-US.vtt 2.58 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/02. Unit of Diversion Overview-Gh32VbXrmdQ.zh-CN.vtt 2.58 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.pt-BR.vtt 2.58 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-6CiZB0N7y64.zh-CN.vtt 2.58 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.en-US.vtt 2.58 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.zh-CN.vtt 2.58 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-DqC-pgcEam4.zh-CN.vtt 2.58 KB
Part 13-Module 01-Lesson 04_Design Principles/25. Communicating with Color-QnFtYKXf7TQ.zh-CN.vtt 2.58 KB
Part 15-Module 01-Lesson 02_Design Principles/13. Communicating with Color-QnFtYKXf7TQ.zh-CN.vtt 2.58 KB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.en.vtt 2.58 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.pt-BR.vtt 2.58 KB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.en.vtt 2.58 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Use Separate Tables-UIQBtpmqYOs.zh-CN.vtt 2.58 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt 2.58 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt 2.58 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.pt-BR.vtt 2.58 KB
Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.ar.vtt 2.58 KB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.ar.vtt 2.58 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.en.vtt 2.58 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment Solution-LhdGQC_vjEs.zh-CN.vtt 2.58 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.ar.vtt 2.58 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.ar.vtt 2.58 KB
Part 12-Module 02-Lesson 05_Trees/19. Red-Black Trees - Insertion-dIuWLtWnkgs.zh-CN.vtt 2.58 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.pt-BR.vtt 2.58 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.en.vtt 2.58 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score-pftNHu4uevA.pt-BR.vtt 2.57 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-K6zJtrTEf6k.zh-CN.vtt 2.57 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.en.vtt 2.57 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.en.vtt 2.57 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.pt-BR.vtt 2.57 KB
Part 13-Module 01-Lesson 07_Narrative Structures/39. Using extent() for scales-oazLw2JhKiU.zh-CN.vtt 2.57 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.en.vtt 2.57 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.pt-BR.vtt 2.57 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.ar.vtt 2.57 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-dtnjREsGfXI.zh-CN.vtt 2.57 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.pt-BR.vtt 2.57 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.zh-CN.vtt 2.57 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-Gl6anQql914.zh-CN.vtt 2.57 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/03. Problems Solved by Data Analysts-zbjRiYSSR_Y.zh-CN.vtt 2.57 KB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.ar.vtt 2.57 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.pt-BR.vtt 2.57 KB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.pt-BR.vtt 2.57 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/13. Binomial Distribution-PVTChqpnr5Q.zh-CN.vtt 2.57 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.pt-BR.vtt 2.57 KB
Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.ar.vtt 2.56 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.zh-CN.vtt 2.56 KB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.ar.vtt 2.56 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.zh-CN.vtt 2.56 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.pt-BR.vtt 2.56 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.en.vtt 2.56 KB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.pt-BR.vtt 2.56 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/03. Your First Subquery-cTM1jPYXLoQ.zh-CN.vtt 2.56 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.ja.vtt 2.56 KB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.ar.vtt 2.56 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.th.vtt 2.56 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.pt-BR.vtt 2.56 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.pt-BR.vtt 2.56 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.pt-BR.vtt 2.56 KB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.ja.vtt 2.56 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/02. Interviewing Conversations-klqXp09Pen4.zh-CN.vtt 2.56 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/01. Introduction to Course-gR_buSP6sdw.zh-CN.vtt 2.56 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.en.vtt 2.55 KB
Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.ar.vtt 2.55 KB
Part 05-Module 02-Lesson 01_Data and Tables/02. What's a Database - Intro to Relational Databases-V4gbPVdUOpw.zh-CN.vtt 2.55 KB
Part 17-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.en.vtt 2.55 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/20. Broken Requests-QFjKVSmxODY.zh-CN.vtt 2.55 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.en.vtt 2.55 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.ar.vtt 2.55 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.en.vtt 2.55 KB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.pt-BR.vtt 2.55 KB
Part 11-Module 01-Lesson 10_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.zh-CN.vtt 2.55 KB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.en-US.vtt 2.55 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.ar.vtt 2.55 KB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.pt-BR.vtt 2.55 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.ar.vtt 2.55 KB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.en.vtt 2.55 KB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.ar.vtt 2.55 KB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.en.vtt 2.54 KB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.en.vtt 2.54 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.ar.vtt 2.54 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.ar.vtt 2.54 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/12. Types Of Errors - Part III-Z-srkCPsdaM.zh-CN.vtt 2.54 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/23. Interpreting Interactions-XV6S2srsdxw.zh-CN.vtt 2.54 KB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.pt-BR.vtt 2.54 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt 2.54 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt 2.54 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.es-MX.vtt 2.54 KB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-EL5z2lUuxY4.zh-CN.vtt 2.54 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.pt-BR.vtt 2.54 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.pt-BR.vtt 2.54 KB
Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.ar.vtt 2.54 KB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.pt-BR.vtt 2.54 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.en.vtt 2.54 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.ar.vtt 2.54 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.pt-BR.vtt 2.54 KB
Part 11-Module 01-Lesson 03_SVM/23. SVM Gamma Parameter-m2a2K4lprQw.zh-CN.vtt 2.54 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.en.vtt 2.54 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/01. Introduction-yod62-mxXR4.zh-CN.vtt 2.54 KB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.pt-BR.vtt 2.53 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt 2.53 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt 2.53 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.en.vtt 2.53 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.ar.vtt 2.53 KB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.en.vtt 2.53 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.en.vtt 2.53 KB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.en.vtt 2.53 KB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.ar.vtt 2.53 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.pt-BR.vtt 2.53 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.pt-BR.vtt 2.53 KB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.pt-BR.vtt 2.53 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.ar.vtt 2.53 KB
Part 11-Module 01-Lesson 09_Clustering/02. Clustering Movies-g8PKffm8IRY.zh-CN.vtt 2.53 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.en.vtt 2.53 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.en.vtt 2.52 KB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.en-US.vtt 2.52 KB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.ar.vtt 2.52 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.en.vtt 2.52 KB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.en.vtt 2.52 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/22. Simulation Applet-yu4mdXybrts.zh-CN.vtt 2.52 KB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.ar.vtt 2.52 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.en-US.vtt 2.52 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.ar.vtt 2.52 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.ar.vtt 2.51 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.en.vtt 2.51 KB
Part 14-Module 01-Lesson 05_Analyzing Results/02. Sanity Checks-OVnlC_T3EpI.zh-CN.vtt 2.51 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.en.vtt 2.51 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/25. Aggregations-ADx1x2ljFB4.zh-CN.vtt 2.51 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.ar.vtt 2.51 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.en.vtt 2.51 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.pt-BR.vtt 2.51 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-BqQbAqok8JU.zh-CN.vtt 2.51 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-BqQbAqok8JU.zh-CN.vtt 2.51 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.en.vtt 2.51 KB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.en.vtt 2.51 KB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-NjuenhkC-44.zh-CN.vtt 2.51 KB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.ar.vtt 2.5 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. Trees-OVeJU18ADmw.zh-CN.vtt 2.5 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.en-US.vtt 2.5 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.pt-BR.vtt 2.5 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-f1fz9cLnetM.zh-CN.vtt 2.5 KB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.pt-BR.vtt 2.5 KB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.pt-BR.vtt 2.5 KB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.en.vtt 2.5 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-bR7EoKjN0EM.zh-CN.vtt 2.5 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.en.vtt 2.5 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.pt-BR.vtt 2.5 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.zh-CN.vtt 2.5 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.en-US.vtt 2.5 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.pt-BR.vtt 2.5 KB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.pt-BR.vtt 2.5 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.en.vtt 2.5 KB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.en.vtt 2.5 KB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.pt-BR.vtt 2.5 KB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.en.vtt 2.5 KB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.ar.vtt 2.5 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.ar.vtt 2.5 KB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.pt-BR.vtt 2.5 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.pt-BR.vtt 2.5 KB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.en.vtt 2.49 KB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.en.vtt 2.49 KB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.pt-BR.vtt 2.49 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.en.vtt 2.49 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.pt-BR.vtt 2.49 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.ar.vtt 2.49 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.ar.vtt 2.49 KB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.en.vtt 2.49 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.en.vtt 2.49 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.pt-BR.vtt 2.49 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/02. Course Format-rVmwPGFtk_Y.zh-CN.vtt 2.49 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/23. Drawing Conclusions Example-yAl58ccwyvU.zh-CN.vtt 2.49 KB
Part 21-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.zh-CN.vtt 2.49 KB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.en-US.vtt 2.49 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.ar.vtt 2.49 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.ar.vtt 2.49 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.en.vtt 2.48 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.pt-BR.vtt 2.48 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.en.vtt 2.48 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.en.vtt 2.48 KB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.en.vtt 2.48 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.ar.vtt 2.48 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.ar.vtt 2.48 KB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.en.vtt 2.48 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.en.vtt 2.48 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.ar.vtt 2.48 KB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.ar.vtt 2.48 KB
Part 11-Module 01-Lesson 07_Regressions/17. Coding It Up-BTFOf2qXy5U.zh-CN.vtt 2.48 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.en.vtt 2.48 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.en.vtt 2.48 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.en.vtt 2.48 KB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.pt-BR.vtt 2.48 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/03. 01 Connecting To Data-zuJPPSlbW2c.en.vtt 2.48 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.en.vtt 2.47 KB
Part 12-Module 01-Lesson 05_Interview Practice/07. Jimmy's Analysis of the Interview-wg535YU4jFw.zh-CN.vtt 2.47 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-AaLIKufl_mY.zh-CN.vtt 2.47 KB
Part 13-Module 01-Lesson 05_Dimple.js/31. Customizing a Dimple Chart-93MgOnKP5m0.zh-CN.vtt 2.47 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.pt-BR.vtt 2.47 KB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.en.vtt 2.47 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.ar.vtt 2.47 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.en.vtt 2.47 KB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.ar.vtt 2.47 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.ja.vtt 2.47 KB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.pt-BR.vtt 2.47 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.pt-BR.vtt 2.47 KB
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-7CVlKQ3UjUI.zh-CN.vtt 2.47 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.pt-BR.vtt 2.47 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.en.vtt 2.47 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.en.vtt 2.47 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/03. How This Lesson Is Structured-xfRtO4aFpv0.zh-CN.vtt 2.47 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.zh-CN.vtt 2.47 KB
Part 13-Module 01-Lesson 07_Narrative Structures/63. Adding Text to the Legend-VPI9MVqGiSM.zh-CN.vtt 2.47 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/45. Fixing the Buttons-NxM_iu4sDxw.zh-CN.vtt 2.47 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.ar.vtt 2.47 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/07. Working In The JavaScript Console-cj4kv_dtqY0.zh-CN.vtt 2.46 KB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.ar.vtt 2.46 KB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.pt-BR.vtt 2.46 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/40. Smoothing the Animation with Transitions-9c8he26k_iY.zh-CN.vtt 2.46 KB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.pt-BR.vtt 2.46 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.pt-BR.vtt 2.46 KB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.en-US.vtt 2.46 KB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.en.vtt 2.46 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.pt-BR.vtt 2.46 KB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.en.vtt 2.46 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/16. Binomial Distribution Conclusion-9gjCYs8f_PU.zh-CN.vtt 2.46 KB
Part 13-Module 01-Lesson 07_Narrative Structures/56. Recap and Data Dependency-00Tz_3_91RU.zh-CN.vtt 2.46 KB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.pt-BR.vtt 2.46 KB
Part 05-Module 01-Lesson 05_Data Quality/07. A Blueprint for Cleaning-3S73cNbhuAk.zh-CN.vtt 2.45 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.pt-BR.vtt 2.45 KB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.ar.vtt 2.45 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.en.vtt 2.45 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/04. Why MongoDB-jjMw4Ju-1CM.zh-CN.vtt 2.45 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.pt-BR.vtt 2.45 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.ar.vtt 2.45 KB
Part 11-Module 01-Lesson 02_Naive Bayes/21. Training and Testing Data-x2dmBUEKQIA.zh-CN.vtt 2.45 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.ar.vtt 2.45 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.ar.vtt 2.45 KB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.ar.vtt 2.45 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.pt-BR.vtt 2.45 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.pt-BR.vtt 2.45 KB
Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.ar.vtt 2.45 KB
Part 12-Module 02-Lesson 01_Introduction and Efficiency/09. Notation Continued-ZeGnkrKZWBQ.zh-CN.vtt 2.45 KB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.pt-BR.vtt 2.45 KB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.en.vtt 2.45 KB
Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.en.vtt 2.45 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.ar.vtt 2.45 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.ar.vtt 2.44 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.es-MX.vtt 2.44 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.pt-BR.vtt 2.44 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.ar.vtt 2.44 KB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.pt-BR.vtt 2.44 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.ar.vtt 2.44 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/26. Klout-3q0oPuWxFpA.zh-CN.vtt 2.44 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.pt-BR.vtt 2.44 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.pt-BR.vtt 2.44 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.en.vtt 2.44 KB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.pt-BR.vtt 2.44 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.en.vtt 2.44 KB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.pt-BR.vtt 2.44 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-AqlvTMZg6HY.zh-CN.vtt 2.44 KB
Part 11-Module 01-Lesson 04_Decision Trees/34. DT Strengths and Weaknesses-KGnhg76iRfI.zh-CN.vtt 2.44 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.en.vtt 2.44 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/09. Questions and Consent-ZmXg42IoG_Q.zh-CN.vtt 2.44 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.ja.vtt 2.44 KB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.en.vtt 2.44 KB
Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.ar.vtt 2.44 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/06. Interpreting Multiplie Linear Regression Coefficients-qRD3OVX8UMM.zh-CN.vtt 2.44 KB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.en.vtt 2.44 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.pt-BR.vtt 2.44 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.en.vtt 2.44 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.pt-BR.vtt 2.43 KB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.pt-BR.vtt 2.43 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.en.vtt 2.43 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.ar.vtt 2.43 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.en.vtt 2.43 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.ar.vtt 2.43 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.ar.vtt 2.43 KB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.ja.vtt 2.43 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.pt-BR.vtt 2.43 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.en.vtt 2.43 KB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.pt-BR.vtt 2.43 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.zh-CN.vtt 2.43 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.pt-BR.vtt 2.43 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.en.vtt 2.43 KB
Part 13-Module 01-Lesson 07_Narrative Structures/36. Circles with Bound __data__-JeJ_glcExUs.zh-CN.vtt 2.42 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/06. Connecting To Data-WmsAtqbwRI0.zh-CN.vtt 2.42 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.ar.vtt 2.42 KB
Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.ar.vtt 2.42 KB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.ar.vtt 2.42 KB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.ar.vtt 2.42 KB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.ar.vtt 2.42 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.pt-BR.vtt 2.42 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.pt-BR.vtt 2.42 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.ar.vtt 2.42 KB
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.zh-CN.vtt 2.42 KB
Part 18-Module 03-Lesson 01_Assessing Data/14. Programatic Assessment -Bk_Ve3-4eps.zh-CN.vtt 2.42 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.en.vtt 2.42 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.pt-BR.vtt 2.42 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.ar.vtt 2.42 KB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.ja.vtt 2.42 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.pt-BR.vtt 2.42 KB
Part 13-Module 01-Lesson 04_Design Principles/22. Encoding Nothing-6bpET1lWVtA.zh-CN.vtt 2.42 KB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.pt-BR.vtt 2.42 KB
Part 16-Module 03-Lesson 01_Basic SQL/34. LIKE Operator-O5z6eWkNip4.pt-BR.vtt 2.42 KB
Part 21-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.zh-CN.vtt 2.42 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.pt-BR.vtt 2.42 KB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ar.vtt 2.42 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.ja.vtt 2.41 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.en.vtt 2.41 KB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.pt-BR.vtt 2.41 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.en-US.vtt 2.41 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.en.vtt 2.41 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.en.vtt 2.41 KB
Part 14-Module 01-Lesson 05_Analyzing Results/19. Lessons Learned-5JjCVTc0FGk.zh-CN.vtt 2.41 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.pt-BR.vtt 2.41 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.ar.vtt 2.41 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/10. Aggregates in Window Functions-Dxew5w3VF7k.zh-CN.vtt 2.41 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.pt-BR.vtt 2.41 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.en.vtt 2.41 KB
Part 04-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.pt-BR.vtt 2.41 KB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.pt-BR.vtt 2.41 KB
Part 16-Module 01-Lesson 02_Jupyter notebooks/01. Jupyter-qiYDWFLyXvg.pt-BR.vtt 2.41 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.pt-BR.vtt 2.41 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.pt-BR.vtt 2.41 KB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.ar.vtt 2.41 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.ar.vtt 2.41 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.ar.vtt 2.41 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.ar.vtt 2.41 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.pt-BR.vtt 2.41 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.pt-BR.vtt 2.41 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.ar.vtt 2.41 KB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.pt-BR.vtt 2.41 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.pt-BR.vtt 2.41 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.pt-BR.vtt 2.41 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.pt-BR.vtt 2.4 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.ar.vtt 2.4 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.ar.vtt 2.4 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.pt-BR.vtt 2.4 KB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.pt-BR.vtt 2.4 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.zh-Hans.vtt 2.4 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/07. Running Totals And Count-rNJwmnzUTxg.zh-CN.vtt 2.4 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt 2.4 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt 2.4 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/06. Resume Review-L3F2BFGYMtI.zh-CN.vtt 2.4 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.ja.vtt 2.4 KB
Part 13-Module 01-Lesson 07_Narrative Structures/27. Defining a Join-Xo-OJXzS0tQ.zh-CN.vtt 2.4 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.en.vtt 2.4 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.pt-BR.vtt 2.4 KB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.pt-BR.vtt 2.4 KB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-eAKVYAR_VlY.en.vtt 2.4 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.en.vtt 2.4 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.zh-CN.vtt 2.4 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-RZPKn5DKB0Q.zh-CN.vtt 2.4 KB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.ja.vtt 2.4 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.en-US.vtt 2.4 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.pt-BR.vtt 2.4 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/06. CSVs in Python-YIDH9HBY3Qk.zh-CN.vtt 2.4 KB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.pt-BR.vtt 2.4 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.en.vtt 2.39 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.ar.vtt 2.39 KB
Part 11-Module 01-Lesson 03_SVM/10. SVM in SKlearn-R7xQtQzkvTk.zh-CN.vtt 2.39 KB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.pt-BR.vtt 2.39 KB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.ja.vtt 2.39 KB
Part 17-Module 01-Lesson 14_Regression/06. Scatter Plots -DvlxZ37O4i8.en.vtt 2.39 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/09. Scatter Plots -DvlxZ37O4i8.en.vtt 2.39 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.en.vtt 2.39 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.en.vtt 2.39 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.en.vtt 2.39 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/12. Target Population Example-kEFp6xIb8cs.zh-CN.vtt 2.39 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/03. 01 Connecting To Data-zuJPPSlbW2c.zh-CN.vtt 2.39 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.pt-BR.vtt 2.39 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.en.vtt 2.39 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.pt-BR.vtt 2.39 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.ar.vtt 2.39 KB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.en.vtt 2.39 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.en.vtt 2.38 KB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.ar.vtt 2.38 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.en.vtt 2.38 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.ar.vtt 2.38 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.ar.vtt 2.38 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.ja.vtt 2.38 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.pt-BR.vtt 2.38 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.ar.vtt 2.38 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/20. Number of Visits in the First Week-5GYA5j1fqBU.zh-CN.vtt 2.38 KB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.en.vtt 2.38 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.en.vtt 2.38 KB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.en.vtt 2.38 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/07. Reshaping Data-zQj_waidR5w.zh-CN.vtt 2.38 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/06. Other Techniques-KsiyW6bPux8.zh-CN.vtt 2.38 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.pt-BR.vtt 2.38 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/40. Calculated Fields-tR-K9Mvd4B0.zh-CN.vtt 2.38 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.pt-BR.vtt 2.38 KB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.en.vtt 2.37 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/22. Random Observed Values-KFIt2OC3wCI.zh-CN.vtt 2.37 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.ja.vtt 2.37 KB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.en-US.vtt 2.37 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.pt-BR.vtt 2.37 KB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.pt-BR.vtt 2.37 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1 Solution -I1enB5CA85Q.zh-CN.vtt 2.37 KB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.en.vtt 2.37 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/02. Window Functions-gp0RPgkDHsQ.zh-CN.vtt 2.37 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/08. Overplotting and Domain Knowledge-DMhldSg2_vs.zh-CN.vtt 2.37 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.en.vtt 2.37 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.ar.vtt 2.37 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.en.vtt 2.37 KB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.en.vtt 2.37 KB
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.zh-CN.vtt 2.37 KB
Part 21-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.zh-CN.vtt 2.36 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.en-US.vtt 2.36 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.pt-BR.vtt 2.36 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.pt-BR.vtt 2.36 KB
Part 17-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.ja.vtt 2.36 KB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.ar.vtt 2.36 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt 2.36 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt 2.36 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.en.vtt 2.36 KB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.pt-BR.vtt 2.36 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.en.vtt 2.36 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/04. Algorithm Options-S-cGZ-FEdjQ.zh-CN.vtt 2.36 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-YZb-Uam-Ics.zh-CN.vtt 2.36 KB
Part 13-Module 01-Lesson 04_Design Principles/36. Less is More-urgyRvfWPtU.zh-CN.vtt 2.36 KB
Part 11-Module 01-Lesson 07_Regressions/34. Comparing Classification and Regression-G_0W912qmGc.zh-CN.vtt 2.36 KB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.pt-BR.vtt 2.36 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/03. Sampling Distributions Confidence Intervals-gICzUhMVymo.zh-CN.vtt 2.36 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.en.vtt 2.35 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/08. Time When You Dealt With Failure-Qb4o_4hCuyg.zh-CN.vtt 2.35 KB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.pt-BR.vtt 2.35 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.en-US.vtt 2.35 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/15. Using mongoimport-JVYH9B6Obpg.zh-CN.vtt 2.35 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.ar.vtt 2.35 KB
Part 21-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.zh-CN.vtt 2.35 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.en.vtt 2.35 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.en.vtt 2.35 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.en.vtt 2.35 KB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.ar.vtt 2.35 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.pt-BR.vtt 2.35 KB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.pt-BR.vtt 2.35 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.pt-BR.vtt 2.35 KB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.ja.vtt 2.35 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/04. Knapsack Problem--xRKazHGtjU.zh-CN.vtt 2.35 KB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.en.vtt 2.35 KB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.pt-BR.vtt 2.35 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.en.vtt 2.35 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML and Trees-766JMEtZCPE.zh-CN.vtt 2.35 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.en.vtt 2.35 KB
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-H7IlFC5wbjk.zh-CN.vtt 2.35 KB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.pt-BR.vtt 2.35 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.ar.vtt 2.34 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/27. Heat Maps-zSSNWZuVG8Y.zh-CN.vtt 2.34 KB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.ar.vtt 2.34 KB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.pt-BR.vtt 2.34 KB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.en.vtt 2.34 KB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.ar.vtt 2.34 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.en.vtt 2.34 KB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.en.vtt 2.34 KB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.pt-BR.vtt 2.34 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.en.vtt 2.34 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.pt-BR.vtt 2.34 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.en.vtt 2.34 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.en.vtt 2.34 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.en.vtt 2.34 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.pt-BR.vtt 2.34 KB
Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.ar.vtt 2.34 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt 2.34 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt 2.34 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/02. Effective Resume Components-AiFcaHRGdEA.zh-CN.vtt 2.34 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.pt-BR.vtt 2.33 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.ar.vtt 2.33 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.pt-BR.vtt 2.33 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.es.vtt 2.33 KB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-ZFn9xVQ0hD4.zh-CN.vtt 2.33 KB
Part 13-Module 01-Lesson 05_Dimple.js/12. Creating and Drawing the Chart-ZyhYNaRqqL0.zh-CN.vtt 2.33 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/26. Where are we-d3jQdOuOy8k.pt-BR.vtt 2.33 KB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.pt-BR.vtt 2.33 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.ar.vtt 2.33 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.pt-BR.vtt 2.33 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.en.vtt 2.33 KB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.pt-BR.vtt 2.33 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.pt-BR.vtt 2.33 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.en.vtt 2.33 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/23. MMs-nCwZE4n4FAs.zh-CN.vtt 2.33 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -zDs_pN7G-wQ.zh-CN.vtt 2.33 KB
Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.pt-BR.vtt 2.33 KB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.pt-BR.vtt 2.33 KB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.en.vtt 2.32 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.pt-BR.vtt 2.32 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.en.vtt 2.32 KB
Part 21-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.zh-CN.vtt 2.32 KB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.ar.vtt 2.32 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.pt-BR.vtt 2.32 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.es.vtt 2.32 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.es.vtt 2.32 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.en.vtt 2.32 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.en.vtt 2.32 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.pt-BR.vtt 2.32 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.pt-BR.vtt 2.32 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.en.vtt 2.32 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.pt-BR.vtt 2.32 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.en.vtt 2.32 KB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.en.vtt 2.31 KB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.pt-BR.vtt 2.31 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt 2.31 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt 2.31 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.en.vtt 2.31 KB
Part 13-Module 01-Lesson 07_Narrative Structures/64. All World Cup Games Recap-tVtEEL5i_BE.en.vtt 2.31 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-vsLtePFaOFY.zh-CN.vtt 2.31 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.ja.vtt 2.31 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-vsLtePFaOFY.zh-CN.vtt 2.31 KB
Part 11-Module 01-Lesson 12_Feature Selection/16. Lasso Regression-qU1_cj4LfLY.zh-CN.vtt 2.31 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.en.vtt 2.31 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 1-J4X9r0EGH3k.zh-CN.vtt 2.31 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.pt-BR.vtt 2.31 KB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.ar.vtt 2.31 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.ar.vtt 2.31 KB
Part 13-Module 01-Lesson 03_Problem Set Visualization Fundamentals/14. What is plot.ly-ZRiAWz-sVlM.zh-CN.vtt 2.31 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.en.vtt 2.31 KB
Part 05-Module 02-Lesson 03_Elements of SQL/10. Why Do It in the Database-6vfZYhhmuLU.zh-CN.vtt 2.31 KB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.ar.vtt 2.31 KB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.pt-BR.vtt 2.31 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.en.vtt 2.3 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.en.vtt 2.3 KB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.ar.vtt 2.3 KB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.en.vtt 2.3 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.en.vtt 2.3 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.ar.vtt 2.3 KB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.en-US.vtt 2.3 KB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.pt-BR.vtt 2.3 KB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.pt-BR.vtt 2.3 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.en.vtt 2.3 KB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.ar.vtt 2.3 KB
Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.ar.vtt 2.3 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.pt-BR.vtt 2.3 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/17. Shape of Distributions-UnN99AAYf8k.zh-CN.vtt 2.3 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.ar.vtt 2.3 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.pt-BR.vtt 2.3 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.ar.vtt 2.3 KB
Part 12-Module 02-Lesson 05_Trees/12. BSTs-abRNGLhGUmE.zh-CN.vtt 2.3 KB
Part 12-Module 02-Lesson 06_Graphs/07. Adjacency Matrices-FsFhoTALA1c.en.vtt 2.3 KB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.en.vtt 2.3 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.pt-BR.vtt 2.3 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.pt-BR.vtt 2.3 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.ar.vtt 2.3 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. Using A Confidence Interval to Make A Decision-MghT95b6LbQ.zh-CN.vtt 2.3 KB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.en-US.vtt 2.3 KB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.en.vtt 2.3 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.ar.vtt 2.29 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.pt-BR.vtt 2.29 KB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.ja.vtt 2.29 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.ar.vtt 2.29 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.ja.vtt 2.29 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.en.vtt 2.29 KB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.en.vtt 2.29 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-Z4n3jR-FZP8.zh-CN.vtt 2.29 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.ja.vtt 2.29 KB
Part 11-Module 01-Lesson 16_Tying It All Together/02. Summary-avqZaTECZTQ.zh-CN.vtt 2.29 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/20. Outliers-HKIsvkZUZfo.zh-CN.vtt 2.29 KB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.pt-BR.vtt 2.29 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.en.vtt 2.29 KB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.en.vtt 2.29 KB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.pt-BR.vtt 2.28 KB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.en.vtt 2.28 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.pt-BR.vtt 2.28 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.en.vtt 2.28 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.es.vtt 2.28 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.es.vtt 2.28 KB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.pt-BR.vtt 2.28 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-4QIEdzv6g6w.en.vtt 2.28 KB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.en.vtt 2.28 KB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.ar.vtt 2.28 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.ar.vtt 2.28 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/05. Setting Up Hypotheses - Part II-nByvHz77GiA.zh-CN.vtt 2.28 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/29. Data Analysis and Related Terms-9g9_tlhbNSw.zh-CN.vtt 2.28 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.pt-BR.vtt 2.28 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/07. DF - Sample SD-Jfk3egev9UM.zh-CN.vtt 2.28 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/02. Job Search Mindset-cBk7bno3KS0.zh-CN.vtt 2.28 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.ar.vtt 2.28 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.pt-BR.vtt 2.28 KB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.ar.vtt 2.28 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.pt-BR.vtt 2.28 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.pt-BR.vtt 2.28 KB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.ar.vtt 2.28 KB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.ar.vtt 2.28 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/08. Assessing Data Sensitivity-UkGwgerJU44.zh-CN.vtt 2.28 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.en.vtt 2.28 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.ar.vtt 2.27 KB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.pt-BR.vtt 2.27 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.ar.vtt 2.27 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.ar.vtt 2.27 KB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.en-US.vtt 2.27 KB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.en.vtt 2.27 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.pt-BR.vtt 2.27 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.pt-BR.vtt 2.27 KB
Part 11-Module 01-Lesson 02_Naive Bayes/17. Getting Started With sklearn-olGPVtH7KGU.pt-BR.vtt 2.27 KB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.en.vtt 2.27 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.en.vtt 2.27 KB
Part 11-Module 01-Lesson 09_Clustering/11. K-Means Clustering Visualization 3-WfwX3B4d8_I.zh-CN.vtt 2.27 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-Hs3__UsSyL8.zh-CN.vtt 2.27 KB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-GtR3dw2eq2w.en.vtt 2.27 KB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.ar.vtt 2.27 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.en.vtt 2.27 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.en.vtt 2.27 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/18. Combining Pandas DataFrames-vB_Et1hz_2M.pt-BR.vtt 2.27 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.pt-BR.vtt 2.27 KB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-GuBics_6HOk.zh-CN.vtt 2.27 KB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.en.vtt 2.27 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.en-US.vtt 2.27 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.ar.vtt 2.27 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/18. Combining Pandas DataFrames-vB_Et1hz_2M.pt-BR.vtt 2.27 KB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.ja.vtt 2.27 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.ar.vtt 2.27 KB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.pt-BR.vtt 2.27 KB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.ar.vtt 2.27 KB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.pt-BR.vtt 2.27 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.ar.vtt 2.26 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.en.vtt 2.26 KB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.en.vtt 2.26 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.ar.vtt 2.26 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.pt-BR.vtt 2.26 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.ar.vtt 2.26 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.pt-BR.vtt 2.26 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.pt-BR.vtt 2.26 KB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.en-US.vtt 2.26 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.pt-BR.vtt 2.26 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/17. Z-Score-pftNHu4uevA.en.vtt 2.26 KB
Part 13-Module 01-Lesson 07_Narrative Structures/11. Personal Data Visualization-NtFICAw7tW4.zh-CN.vtt 2.26 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-WkInrWZwbNA.en.vtt 2.26 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.en.vtt 2.26 KB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.en.vtt 2.26 KB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.pt-BR.vtt 2.26 KB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.ar.vtt 2.26 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/02. Hypothesis Testing-9GbHHpiK6wk.zh-CN.vtt 2.26 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.en.vtt 2.26 KB
Part 12-Module 02-Lesson 05_Trees/03. Tree Terminology-mPUsDUR_sj8.zh-CN.vtt 2.26 KB
Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.en.vtt 2.26 KB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.en.vtt 2.26 KB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.ar.vtt 2.26 KB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.pt-BR.vtt 2.26 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.ar.vtt 2.26 KB
Part 11-Module 01-Lesson 07_Regressions/20. Extracting Score Data from sklearn-NhD4oUuhvO8.zh-CN.vtt 2.25 KB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.en.vtt 2.25 KB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.en.vtt 2.25 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/18. 08 Table Calculations-Vkf3Ft93zMc.pt-BR.vtt 2.25 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.ar.vtt 2.25 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.ar.vtt 2.25 KB
Part 13-Module 01-Lesson 04_Design Principles/47. Discovery versus Presentation-znQ3iBhhJtA.zh-CN.vtt 2.25 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.en.vtt 2.25 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.en.vtt 2.25 KB
Part 17-Module 01-Lesson 16_Logistic Regression/07. Interpreting Results in Python-IY88UTiJltQ.zh-CN.vtt 2.25 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.pt-BR.vtt 2.25 KB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.en.vtt 2.25 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-CfDLpojt4AY.zh-CN.vtt 2.25 KB
Part 17-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.zh-CN.vtt 2.25 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.pt-BR.vtt 2.25 KB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.pt-BR.vtt 2.25 KB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.pt-BR.vtt 2.25 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.ja.vtt 2.25 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/37. setInterval and clearInterval-r1sgfqg85us.zh-CN.vtt 2.25 KB
Part 11-Module 01-Lesson 04_Decision Trees/13. Data Impurity and Entropy-Bd15qhUrKCI.en.vtt 2.25 KB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.pt-BR.vtt 2.25 KB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.pt-BR.vtt 2.25 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.es-MX.vtt 2.24 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.pt-BR.vtt 2.24 KB
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-tfYAGBIR_Ws.zh-CN.vtt 2.24 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.pt-BR.vtt 2.24 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.pt-BR.vtt 2.24 KB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.pt-BR.vtt 2.24 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/03. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.zh-CN.vtt 2.24 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/04. One-Dimensional Data in NumPy and Pandas-hDGFrCaAptM.zh-CN.vtt 2.24 KB
Part 12-Module 02-Lesson 06_Graphs/03. Directions and Cycles-lF0vUktQDPo.zh-CN.vtt 2.24 KB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.ar.vtt 2.24 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.pt-BR.vtt 2.24 KB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.ar.vtt 2.24 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-cgWAzXtglF0.en.vtt 2.24 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.pt-BR.vtt 2.24 KB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.en.vtt 2.24 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.ar.vtt 2.24 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/04. What You Can and Can't Do with AB Tests-EwV5Vs2m33w.zh-CN.vtt 2.24 KB
Part 09-Module 01-Lesson 03_Explore One Variable/26. Box Plots-Hk26Zn3xQEY.zh-CN.vtt 2.23 KB
Part 12-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.zh-CN.vtt 2.23 KB
Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.en.vtt 2.23 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.ar.vtt 2.23 KB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.ar.vtt 2.23 KB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.en.vtt 2.23 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.ar.vtt 2.23 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.pt-BR.vtt 2.23 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.pt-BR.vtt 2.23 KB
Part 05-Module 01-Lesson 05_Data Quality/05. Measuring Data Quality-dj46LqDBFYM.zh-CN.vtt 2.23 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.en.vtt 2.23 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.ar.vtt 2.23 KB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.en-US.vtt 2.23 KB
Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.ar.vtt 2.23 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.pt-BR.vtt 2.23 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/03. Third Qualitative Variable-qXvnpC2UdVU.zh-CN.vtt 2.23 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.pt-BR.vtt 2.23 KB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.en.vtt 2.23 KB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.pt-BR.vtt 2.23 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/02. Multiple Linear Regression-rvYZp99nj6c.zh-CN.vtt 2.23 KB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.en.vtt 2.23 KB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.es.vtt 2.23 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.en.vtt 2.23 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.ar.vtt 2.23 KB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.ab.vtt 2.22 KB
Part 12-Module 02-Lesson 06_Graphs/06. Graph Representations-uw9u6dtl0WA.zh-CN.vtt 2.22 KB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.en.vtt 2.22 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.zh-CN.vtt 2.22 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.en.vtt 2.22 KB
Part 17-Module 01-Lesson 14_Regression/10. What Defines A Line-lTqwhsSNP2c.zh-CN.vtt 2.22 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/21. One tailed or two tailed-Cf8PvkUR1NQ.zh-CN.vtt 2.22 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.en.vtt 2.22 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.en-US.vtt 2.22 KB
Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.ar.vtt 2.22 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.pt-BR.vtt 2.22 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.ar.vtt 2.22 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.en-US.vtt 2.22 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.ar.vtt 2.22 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.pt-BR.vtt 2.22 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/07. Packages Overview-sCQoQsmI3F0.zh-CN.vtt 2.22 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.en.vtt 2.22 KB
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-ihC1Pm8E8gU.zh-CN.vtt 2.22 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.en.vtt 2.22 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.pt-BR.vtt 2.22 KB
Part 08-Module 01-Lesson 01_Conduct a Job Search/01. Introduction-axcFtHK6If4.zh-CN.vtt 2.22 KB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.en.vtt 2.22 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.en.vtt 2.22 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.en.vtt 2.22 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.pt-BR.vtt 2.22 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/07. What is the Standard Deviation Measuring-IbwUJ3ORZ5s.zh-CN.vtt 2.22 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.pt-BR.vtt 2.22 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.ar.vtt 2.22 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.en.vtt 2.21 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.pt-BR.vtt 2.21 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.en.vtt 2.21 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.ja.vtt 2.21 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.pt-BR.vtt 2.21 KB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.ar.vtt 2.21 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.pt-BR.vtt 2.21 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.pt-BR.vtt 2.21 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.zh-CN.vtt 2.21 KB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-vpwCy5Gphrw.pt-BR.vtt 2.21 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.ar.vtt 2.21 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-R5EsIDJ0apw.en.vtt 2.21 KB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.pt-BR.vtt 2.21 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.ar.vtt 2.21 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.ar.vtt 2.21 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.en.vtt 2.21 KB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.ar.vtt 2.21 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.pt-BR.vtt 2.21 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.ar.vtt 2.21 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. Assess Intro -vj3CYBlWj3k.zh-CN.vtt 2.21 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.ar.vtt 2.21 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.en.vtt 2.2 KB
Part 11-Module 01-Lesson 13_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.en.vtt 2.2 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.ar.vtt 2.2 KB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-VYwgHHqaUII.zh-CN.vtt 2.2 KB
Part 09-Module 01-Lesson 03_Explore One Variable/24. Frequency Polygons-bDRGbJP7YMY.zh-CN.vtt 2.2 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-j3RQ-8l2nos.en.vtt 2.2 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-H-1atcURVzk.en.vtt 2.2 KB
Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.pt-BR.vtt 2.2 KB
Part 12-Module 02-Lesson 05_Trees/05. Tree Traversal-KZOdmzypynw.zh-CN.vtt 2.2 KB
Part 09-Module 01-Lesson 02_R Basics/02. Why R-VlJnNSeO1uQ.zh-CN.vtt 2.2 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.pt-BR.vtt 2.2 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.th.vtt 2.2 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/09. Gather Open Jupyter Notebook-IaExjsrVMgQ.zh-CN.vtt 2.2 KB
Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.en.vtt 2.2 KB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.en.vtt 2.2 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.en.vtt 2.2 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.en.vtt 2.19 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.ar.vtt 2.19 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.ar.vtt 2.19 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.pt-BR.vtt 2.19 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.en.vtt 2.19 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.zh-CN.vtt 2.19 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.en.vtt 2.19 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.ja.vtt 2.19 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.ja.vtt 2.19 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/04. Gathering Data-r7BHGq_0P9Q.pt-BR.vtt 2.19 KB
Part 06-Module 01-Lesson 03_Analyzing Data/08. Match Operator-FZ8KVv1VOK4.zh-CN.vtt 2.19 KB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.ar.vtt 2.19 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.pt-BR.vtt 2.19 KB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.ar.vtt 2.19 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.ar.vtt 2.19 KB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.en.vtt 2.19 KB
Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.ar.vtt 2.19 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.en.vtt 2.19 KB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.pt-BR.vtt 2.19 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.pt-BR.vtt 2.19 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.ar.vtt 2.19 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.ar.vtt 2.19 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.ar.vtt 2.19 KB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.pt-BR.vtt 2.19 KB
Part 12-Module 02-Lesson 05_Trees/17. Heap Implementation-2LAdml6_pDY.zh-CN.vtt 2.19 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/43. Table Calculations-VJfCNO0J9jY.zh-CN.vtt 2.19 KB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.pt-BR.vtt 2.19 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.hi.vtt 2.18 KB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.ar.vtt 2.18 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/11. Moira Histogram Summary Scatterplots-GmR3uEM189M.zh-CN.vtt 2.18 KB
Part 13-Module 01-Lesson 04_Design Principles/35. Chartjunk-jm2qOX2Q2HQ.pt-BR.vtt 2.18 KB
Part 15-Module 01-Lesson 02_Design Principles/16. Gráfico Lixo-jm2qOX2Q2HQ.pt-BR.vtt 2.18 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.en.vtt 2.18 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-O0zo3-NtBSI.en.vtt 2.18 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/14. Common Types of Hypothesis Tests-8hv8KnvQ6JY.zh-CN.vtt 2.18 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.pt-BR.vtt 2.18 KB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.pt-BR.vtt 2.18 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.en.vtt 2.18 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/17. Type And Quality Plot - Part 2-Ui1rF6McOBA.zh-CN.vtt 2.18 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.pt-BR.vtt 2.18 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.pt-BR.vtt 2.18 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.ar.vtt 2.18 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.pt-BR.vtt 2.18 KB
Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.en.vtt 2.18 KB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.en.vtt 2.18 KB
Part 21-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.zh-CN.vtt 2.18 KB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.pt-BR.vtt 2.17 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.pt-BR.vtt 2.17 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.en.vtt 2.17 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.pt-BR.vtt 2.17 KB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-StmEUgT1XSY.en.vtt 2.17 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt 2.17 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.en.vtt 2.17 KB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.ar.vtt 2.17 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.en.vtt 2.17 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators-48AgxPygRuQ.en.vtt 2.17 KB
Part 12-Module 02-Lesson 05_Trees/20. Tree Rotations-O5Yl-m0YbVA.zh-CN.vtt 2.17 KB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.en.vtt 2.17 KB
Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.ar.vtt 2.17 KB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.pt-BR.vtt 2.17 KB
Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.ar.vtt 2.17 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.es-ES.vtt 2.17 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/26. Confidence Interval Case Breakdown-gycmvQqw-8s.en.vtt 2.17 KB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.en.vtt 2.17 KB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.pt-BR.vtt 2.17 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.pt-BR.vtt 2.17 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.en.vtt 2.17 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.en.vtt 2.17 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.en.vtt 2.17 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt 2.17 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt 2.17 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.pt-BR.vtt 2.17 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/10. Scatterplot Transformation-h1wbEPuADz0.zh-CN.vtt 2.17 KB
Part 13-Module 01-Lesson 07_Narrative Structures/42. I Love Data Visualization-j24CoLV675I.zh-CN.vtt 2.17 KB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.ar.vtt 2.16 KB
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.pt-BR.vtt 2.16 KB
Part 13-Module 01-Lesson 04_Design Principles/54. The Spectrum of Tech in Data Vis-4-tLvLvX9U4.zh-CN.vtt 2.16 KB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.en.vtt 2.16 KB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.ar.vtt 2.16 KB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.en.vtt 2.16 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-ONhDQKYCJlE.zh-CN.vtt 2.16 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.ja.vtt 2.16 KB
Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.en.vtt 2.16 KB
Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt 2.16 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.ar.vtt 2.16 KB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.pt-BR.vtt 2.16 KB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-SwbreslrpqQ.zh-CN.vtt 2.16 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/02. Tuskegee and Milgram Experiments-mxNp8_3syVk.zh-CN.vtt 2.16 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.en.vtt 2.16 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.ar.vtt 2.16 KB
Part 03-Module 01-Lesson 11_L4 Variability/35. Point of SD-d-_ZKyocTDw.en.vtt 2.16 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/15. Nest Function-rwDTbptCnM4.zh-CN.vtt 2.16 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.ar.vtt 2.15 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-Mta8Hv36k7Q.zh-CN.vtt 2.15 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/03. Facebook Experiment-VqLX0wnrldc.zh-CN.vtt 2.15 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.en.vtt 2.15 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-Mta8Hv36k7Q.zh-CN.vtt 2.15 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.en.vtt 2.15 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.en.vtt 2.15 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.ar.vtt 2.15 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/31. What Do You Get with a Good Klout Score-7N7MBPJKCfw.zh-CN.vtt 2.15 KB
Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.pt-BR.vtt 2.15 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.pt-BR.vtt 2.15 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.ar.vtt 2.15 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.pt-BR.vtt 2.15 KB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.ja.vtt 2.15 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/29. Why D3-2qZ3d2WOvwE.zh-CN.vtt 2.15 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/11. Gather CSV Files-FpWi4tExVwg.zh-CN.vtt 2.15 KB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.pt-BR.vtt 2.15 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.en.vtt 2.15 KB
Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.ar.vtt 2.14 KB
Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.ar.vtt 2.14 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.en.vtt 2.14 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.en.vtt 2.14 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.ar.vtt 2.14 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.zh-CN.vtt 2.14 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.es.vtt 2.14 KB
Part 03-Module 01-Lesson 11_L4 Variability/39. Clarifying Sample SD-iRudjk53deY.en.vtt 2.14 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.ar.vtt 2.14 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/11. Introducing the Working Example-ax7aaLNZkPA.zh-CN.vtt 2.14 KB
Part 13-Module 01-Lesson 07_Narrative Structures/55. Attendance at Every World Cup Game-LuCV0YuhoZE.zh-CN.vtt 2.14 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/21. Working with Outliers-4RnQjtJB8t8.en.vtt 2.14 KB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.en.vtt 2.14 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.pt-BR.vtt 2.14 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.pt-BR.vtt 2.14 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/11. Metric - Average Reading Duration-w6Y9ZxHDEbw.zh-CN.vtt 2.14 KB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.ja.vtt 2.14 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/02. Lesson Overview-1EzlGH4Biu0.zh-CN.vtt 2.14 KB
Part 17-Module 01-Lesson 14_Regression/16. How Do We Interpret Results-eLk0XGGMaCE.zh-CN.vtt 2.14 KB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.ar.vtt 2.14 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.en.vtt 2.14 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.pt-BR.vtt 2.14 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-gpwlI9Wa8xI.zh-CN.vtt 2.14 KB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.ar.vtt 2.14 KB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.pt-BR.vtt 2.14 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.en-US.vtt 2.13 KB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.pt-BR.vtt 2.13 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/07. Univariate Plots-kgmYLreYB0A.zh-CN.vtt 2.13 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.en.vtt 2.13 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.ja.vtt 2.13 KB
Part 11-Module 01-Lesson 11_Text Learning/14. Why Upweight Rare Words-xYQb6f1SIEk.pt-BR.vtt 2.13 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Solution -lJEMTES2Ar8.zh-CN.vtt 2.13 KB
Part 21-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.zh-CN.vtt 2.13 KB
Part 13-Module 01-Lesson 04_Design Principles/31. Red Green Color Blindness-iqbqj9kbapM.zh-CN.vtt 2.13 KB
Part 13-Module 01-Lesson 07_Narrative Structures/50. The Anonymous Accessor Function-I4niz8YMMUM.zh-CN.vtt 2.13 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.es.vtt 2.13 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.ar.vtt 2.13 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.pt-BR.vtt 2.13 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.ar.vtt 2.13 KB
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-S-pjRUJAGTs.zh-CN.vtt 2.13 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.en.vtt 2.13 KB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.en.vtt 2.13 KB
Part 19-Module 01-Lesson 02_Design/16. General Design Tips-Zq-wMwOfQqY.zh-CN.vtt 2.13 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.zh-CN.vtt 2.13 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.pt-BR.vtt 2.13 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.ja.vtt 2.13 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-YaznAtppruA.en.vtt 2.13 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.pt-BR.vtt 2.13 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.pt-BR.vtt 2.13 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.pt-BR.vtt 2.13 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.pt-BR.vtt 2.13 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.pt-BR.vtt 2.13 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.ja.vtt 2.13 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.en.vtt 2.13 KB
Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.pt-BR.vtt 2.13 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/05. Experiment I-JLKAdT2JESk.zh-CN.vtt 2.13 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.es-ES.vtt 2.13 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.pt-BR.vtt 2.13 KB
Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.ar.vtt 2.13 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/17. Introducing the Yogurt Dataset-5J9GxnJVo78.zh-CN.vtt 2.12 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/13. Calculating the Mean-1nzZxmJ8xvU.zh-CN.vtt 2.12 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.zh-CN.vtt 2.12 KB
Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.pt-BR.vtt 2.12 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.en.vtt 2.12 KB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.ja.vtt 2.12 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.zh-CN.vtt 2.12 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.en.vtt 2.12 KB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.pt-BR.vtt 2.12 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/05. Investigation Process-5o2x4UsumLY.zh-CN.vtt 2.12 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/06. Words of Wisdom from Zipfian Academy-ani9_ZalK-8.zh-CN.vtt 2.12 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/24. Drawing Circles-GlIXt29deCA.zh-CN.vtt 2.12 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.ar.vtt 2.12 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-OB7iJnEY0Tg.zh-CN.vtt 2.12 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.pt-BR.vtt 2.12 KB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.pt-BR.vtt 2.11 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.en.vtt 2.11 KB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.pt-BR.vtt 2.11 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.zh-CN.vtt 2.11 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.en.vtt 2.11 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.it.vtt 2.11 KB
Part 17-Module 01-Lesson 16_Logistic Regression/02. Fitting Logistic Regression-Dg0rBDQnIYg.zh-CN.vtt 2.11 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.en.vtt 2.11 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.pt-BR.vtt 2.11 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.en-US.vtt 2.11 KB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.ja.vtt 2.11 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.en.vtt 2.11 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.ar.vtt 2.11 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/07. What Do You Know About the Company-CcTfHemUvbM.zh-CN.vtt 2.11 KB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.pt-BR.vtt 2.11 KB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.pt-BR.vtt 2.11 KB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.ar.vtt 2.11 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.es.vtt 2.11 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.es.vtt 2.11 KB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.en.vtt 2.11 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.en.vtt 2.11 KB
Part 13-Module 01-Lesson 07_Narrative Structures/48. Adding the Axes to the Page-B3qrRUamyUs.zh-CN.vtt 2.11 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-PBcd_dxiFbE.pt-BR.vtt 2.11 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.pt-BR.vtt 2.11 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.en-US.vtt 2.11 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.en.vtt 2.11 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.en.vtt 2.11 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.en.vtt 2.1 KB
Part 11-Module 01-Lesson 02_Naive Bayes/02. Acerous Vs. Non-Acerous-M5pj2CrO-2w.zh-CN.vtt 2.1 KB
Part 12-Module 02-Lesson 05_Trees/18. Self-Balancing Trees-EHI548K3jiw.zh-CN.vtt 2.1 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.es-ES.vtt 2.1 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/26. Predicting Based on Many Features-oZqGlJbRZu4.zh-CN.vtt 2.1 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt 2.1 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt 2.1 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.es-MX.vtt 2.1 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.en.vtt 2.1 KB
Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.pt-BR.vtt 2.1 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.en.vtt 2.1 KB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.en.vtt 2.1 KB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.pt-BR.vtt 2.1 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.pt-BR.vtt 2.1 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-NSuT87J4V-g.en.vtt 2.1 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt 2.1 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt 2.1 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.zh-CN.vtt 2.1 KB
Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.pt-BR.vtt 2.1 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.pt-BR.vtt 2.1 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-EtWewV65zbs.zh-CN.vtt 2.1 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ivBGyL3SzO0.zh-CN.vtt 2.1 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.en.vtt 2.1 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.pt-BR.vtt 2.1 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.ar.vtt 2.1 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.pt-BR.vtt 2.1 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.zh-CN.vtt 2.1 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.en.vtt 2.09 KB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.ar.vtt 2.09 KB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.it.vtt 2.09 KB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.ar.vtt 2.09 KB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.ar.vtt 2.09 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.pt-BR.vtt 2.09 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/06. Critical Regions-UF3japjNx98.zh-CN.vtt 2.09 KB
Part 05-Module 02-Lesson 03_Elements of SQL/03. Types in the SQL World-8swA-PqlEP0.zh-CN.vtt 2.09 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.zh-CN.vtt 2.09 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.en.vtt 2.09 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.pt-BR.vtt 2.09 KB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.pt-BR.vtt 2.09 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/22. Scraping Solution-J1gn4ZBLkt4.zh-CN.vtt 2.09 KB
Part 13-Module 01-Lesson 05_Dimple.js/02. World Cup Data-1Hd1Bq1YxXg.en.vtt 2.09 KB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.en.vtt 2.09 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.ar.vtt 2.09 KB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-NvgWKf-iBsw.zh-CN.vtt 2.09 KB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.ar.vtt 2.09 KB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.pt-BR.vtt 2.09 KB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.en.vtt 2.09 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/10. Estimating Click-Through-Probability-Hkbc_vcb7D8.zh-CN.vtt 2.09 KB
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.en.vtt 2.08 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.ar.vtt 2.08 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/12. Projection Queries-dFGlIC9nI1Q.zh-CN.vtt 2.08 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.pt-BR.vtt 2.08 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/34. From Source Code to Graphic-PIqgFTee-lk.zh-CN.vtt 2.08 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.ar.vtt 2.08 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.ar.vtt 2.08 KB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.pt-BR.vtt 2.08 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/08. Self JOINs-tw_VzEGBOvI.zh-CN.vtt 2.08 KB
Part 03-Module 01-Lesson 20_L8 Estimation/01. Summary-51hx5u2EMZA.zh-CN.vtt 2.08 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-wZDgVcAW_es.zh-CN.vtt 2.08 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.pt-BR.vtt 2.08 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.ar.vtt 2.08 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt 2.08 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt 2.08 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/01. Convey Your Skills Concisely-xnQr3ohml9s.zh-CN.vtt 2.08 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.pt-BR.vtt 2.08 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.pt-BR.vtt 2.08 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.pt-BR.vtt 2.08 KB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.es-MX.vtt 2.08 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/01. What is Data Visualization-mfLklbVU7r0.zh-CN.vtt 2.08 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/23. Keeping Trust and Drawing Circles-pBLeU5bbKak.zh-CN.vtt 2.08 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.pt-BR.vtt 2.08 KB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.ar.vtt 2.08 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.en.vtt 2.08 KB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.ar.vtt 2.08 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.ja.vtt 2.08 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.ar.vtt 2.08 KB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.pt-BR.vtt 2.08 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.pt-BR.vtt 2.08 KB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.en.vtt 2.08 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.pt-BR.vtt 2.07 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.ar.vtt 2.07 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.pt-BR.vtt 2.07 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.pt-BR.vtt 2.07 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.en.vtt 2.07 KB
Part 07-Module 01-Lesson 01_GitHub Review/09. Interview with Art - Part 2-Vvzl2J5K7-Y.zh-CN.vtt 2.07 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.en.vtt 2.07 KB
Part 12-Module 01-Lesson 05_Interview Practice/05. Maximum Difference in an Integer Array-R9AtVBq2Z5E.zh-CN.vtt 2.07 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.pt-BR.vtt 2.07 KB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.pt-BR.vtt 2.07 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.pt-BR.vtt 2.07 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-WnQoZzxas-g.zh-CN.vtt 2.07 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.zh-CN.vtt 2.07 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.ar.vtt 2.07 KB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.ja.vtt 2.07 KB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.ar.vtt 2.07 KB
Part 13-Module 01-Lesson 07_Narrative Structures/47. Creating Axes-3jEbyeW1Re4.zh-CN.vtt 2.07 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.ar.vtt 2.07 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.en-US.vtt 2.07 KB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.pt-BR.vtt 2.07 KB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.pt-BR.vtt 2.07 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.en.vtt 2.07 KB
Part 13-Module 01-Lesson 05_Dimple.js/23. Changing the Date Format-_jOLSNoKxhQ.zh-CN.vtt 2.07 KB
Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.ar.vtt 2.07 KB
Part 07-Module 01-Lesson 01_GitHub Review/03. Good GitHub repository-qBi8Q1EJdfQ.pt-BR.vtt 2.07 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.en.vtt 2.07 KB
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.en.vtt 2.07 KB
Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.ar.vtt 2.07 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.en.vtt 2.07 KB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.ar.vtt 2.07 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/12. Introduction to Summary Statistics-PCZmHCrcMcw.zh-CN.vtt 2.07 KB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.en.vtt 2.06 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-WCcnGQY771c.pt-BR.vtt 2.06 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-WCcnGQY771c.pt-BR.vtt 2.06 KB
Part 05-Module 01-Lesson 05_Data Quality/09. Auditing Validity-B9vjn8IYaSg.zh-CN.vtt 2.06 KB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.zh-CN.vtt 2.06 KB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.ar.vtt 2.06 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.en-US.vtt 2.06 KB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.en.vtt 2.06 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.en.vtt 2.06 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.zh-CN.vtt 2.06 KB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.pt-BR.vtt 2.06 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.ar.vtt 2.06 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/12. Pandas Groupby-aWc18hHpXRk.zh-CN.vtt 2.06 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/02. Introduction Part II-2ldF64FPWw4.zh-CN.vtt 2.06 KB
Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.en-US.vtt 2.06 KB
Part 16-Module 03-Lesson 01_Basic SQL/06. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt 2.06 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Why Businesses Choose Databases-j4ey7--h9r8.zh-CN.vtt 2.06 KB
Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.en-US.vtt 2.06 KB
Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.pt-BR.vtt 2.06 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.en.vtt 2.06 KB
Part 14-Module 01-Lesson 05_Analyzing Results/03. Choosing Invariants-qCnbDgy2yHk.pt-BR.vtt 2.06 KB
Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.en.vtt 2.06 KB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.ja.vtt 2.06 KB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.en.vtt 2.06 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.zh-CN.vtt 2.06 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.en.vtt 2.06 KB
Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.en.vtt 2.06 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Solution --faitcQ7SKs.zh-CN.vtt 2.06 KB
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-80aFO4KmcPM.zh-CN.vtt 2.05 KB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.en.vtt 2.05 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/28. Assumptions-CdoWdNAKSYw.zh-CN.vtt 2.05 KB
Part 13-Module 01-Lesson 07_Narrative Structures/18. Author-driven Examples-mr2HGcqk3nU.zh-CN.vtt 2.05 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.en.vtt 2.05 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.en.vtt 2.05 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.en.vtt 2.05 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.ar.vtt 2.05 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.en.vtt 2.05 KB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.ar.vtt 2.05 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-lVLgiRRhFpQ.en.vtt 2.05 KB
Part 12-Module 02-Lesson 06_Graphs/11. BFS-pol4kGNlvJA.zh-CN.vtt 2.05 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-KYa8_fuZ30w.zh-CN.vtt 2.05 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.en.vtt 2.05 KB
Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.ar.vtt 2.05 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.ar.vtt 2.05 KB
Part 16-Module 03-Lesson 01_Basic SQL/24. WHERE Statements -mN0uTnlXaxg.zh-CN.vtt 2.05 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.en.vtt 2.05 KB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.th.vtt 2.05 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.en.vtt 2.05 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/16. Pandas groupby()-w3D0no7E8uw.en.vtt 2.05 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.en.vtt 2.05 KB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.pt-BR.vtt 2.05 KB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.ar.vtt 2.04 KB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.pt-BR.vtt 2.04 KB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.ar.vtt 2.04 KB
Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.ar.vtt 2.04 KB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.ar.vtt 2.04 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Scraping Webpages -bAeGbBBAIkE.pt-BR.vtt 2.04 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.en.vtt 2.04 KB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.en.vtt 2.04 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/06. Choosing Metrics-mOH45PzylKk.zh-CN.vtt 2.04 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.en.vtt 2.04 KB
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/01. Intro-vek87HVWexE.zh-CN.vtt 2.04 KB
Part 06-Module 01-Lesson 05_Case Study OpenStreetMap Data/01. Intro-vek87HVWexE.zh-CN.vtt 2.04 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/02. Sets and Maps-gmIb-qZhTDQ.zh-CN.vtt 2.04 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/17. Collecting Stadium Locations-CqE3Zqv21Wo.zh-CN.vtt 2.04 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/18. 39. SAD-tya_avP-hKc.zh-CN.vtt 2.04 KB
Part 09-Module 01-Lesson 02_R Basics/09. Getting Help-ABVX527RODE.zh-CN.vtt 2.04 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-t_ZSrov187k.en.vtt 2.04 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.ar.vtt 2.04 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.ja.vtt 2.04 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.ar.vtt 2.04 KB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.en.vtt 2.04 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.pt-BR.vtt 2.04 KB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.ja.vtt 2.04 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.ar.vtt 2.04 KB
Part 16-Module 03-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.zh-CN.vtt 2.04 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ar.vtt 2.04 KB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.ar.vtt 2.04 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.pt-BR.vtt 2.04 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/14. Refining the Question-P8ZxaAQTZXQ.pt-BR.vtt 2.04 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/20. Building the Linear Model-zyIc0sXYk2A.en.vtt 2.04 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.en.vtt 2.04 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.ar.vtt 2.04 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/13. Thematic Maps-Jw2q-B2kM9k.zh-CN.vtt 2.04 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.pt-BR.vtt 2.03 KB
Part 19-Module 01-Lesson 02_Design/06. What Experts Say About Visual Encodings-98aog0eVcC4.zh-CN.vtt 2.03 KB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.en.vtt 2.03 KB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.en.vtt 2.03 KB
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.pt-BR.vtt 2.03 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-FpcCdcKFBKM.en.vtt 2.03 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.pt-BR.vtt 2.03 KB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.en.vtt 2.03 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.ar.vtt 2.03 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.pt-BR.vtt 2.03 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test-IdP9Ps2tHgw.pt-BR.vtt 2.03 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.ar.vtt 2.03 KB
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-B_fHrMIzIgE.ja.vtt 2.03 KB
Part 16-Module 03-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.zh-CN.vtt 2.03 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.pt-BR.vtt 2.03 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/06. Gather Intro-K5ITQn1L1R0.zh-CN.vtt 2.03 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.pt-BR.vtt 2.03 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-9v9zh0O_0go.ja.vtt 2.03 KB
Part 13-Module 01-Lesson 04_Design Principles/03. Parts of Speech Analogy for Data Vis-bO8clma7Mnc.en.vtt 2.03 KB
Part 21-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.en.vtt 2.03 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.ar.vtt 2.03 KB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.en.vtt 2.03 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/19. Checking the Nest Return-hCXhsYVLqig.zh-CN.vtt 2.03 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.es.vtt 2.03 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.ar.vtt 2.03 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.en.vtt 2.02 KB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.ar.vtt 2.02 KB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.en.vtt 2.02 KB
Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.en.vtt 2.02 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.ar.vtt 2.02 KB
Part 11-Module 01-Lesson 07_Regressions/35. Multivariate Regression Quiz-YPPQy_eB2mU.zh-CN.vtt 2.02 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/12. Iterating on Visualizations-muh0thR2DKo.zh-CN.vtt 2.02 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.ar.vtt 2.02 KB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-AY5nywPa3GI.ja.vtt 2.02 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-DclTt9xqS4s.en.vtt 2.02 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.en.vtt 2.02 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-uCRzrlaA8mg.zh-CN.vtt 2.02 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.pt-BR.vtt 2.02 KB
Part 14-Module 01-Lesson 05_Analyzing Results/13. Multiple Metrics Example-0eCWo0h5DpM.zh-CN.vtt 2.02 KB
Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.pt-BR.vtt 2.02 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/02. Clarifying the Question-XvvKBmKC_84.pt-BR.vtt 2.02 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.ar.vtt 2.02 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.en-US.vtt 2.02 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.en.vtt 2.02 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.pt-BR.vtt 2.02 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.pt-BR.vtt 2.02 KB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.en.vtt 2.02 KB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.pt-BR.vtt 2.02 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.en-US.vtt 2.02 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/31. Small Multiples And Dual Axis-bx6MxsoDqsI.zh-CN.vtt 2.02 KB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-apqUAtnsLZE.zh-CN.vtt 2.02 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.pt-BR.vtt 2.02 KB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.pt-BR.vtt 2.02 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.en.vtt 2.02 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.pt-BR.vtt 2.02 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.en.vtt 2.02 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.ar.vtt 2.02 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.en.vtt 2.02 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.en.vtt 2.02 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/25. Sorting the Data for Drawing Order-X-zVfcuacD4.pt-BR.vtt 2.02 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/29. Formula for Location of Median-h3zyZHNyreM.en.vtt 2.01 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.en.vtt 2.01 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.ja.vtt 2.01 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.en.vtt 2.01 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.ja.vtt 2.01 KB
Part 13-Module 01-Lesson 05_Dimple.js/17. Inspecting the X-axis-huZPg2gRmLk.zh-CN.vtt 2.01 KB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.ar.vtt 2.01 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.pt-BR.vtt 2.01 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/17. Moira on Correlation-2vql64jk77I.zh-CN.vtt 2.01 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.ar.vtt 2.01 KB
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-_7Vqou7k7fI.zh-CN.vtt 2.01 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.pt-BR.vtt 2.01 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.pt-BR.vtt 2.01 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.es-ES.vtt 2.01 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.pt-BR.vtt 2.01 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces--VxKwVvrNY0.zh-CN.vtt 2.01 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.pt-BR.vtt 2.01 KB
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces--VxKwVvrNY0.zh-CN.vtt 2.01 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-XDvus8zHJbA.zh-CN.vtt 2.01 KB
Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.en.vtt 2.01 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.ar.vtt 2.01 KB
Part 11-Module 01-Lesson 03_SVM/25. SVM Strengths and Weaknesses-U9-ZsbaaGAs.zh-CN.vtt 2.01 KB
Part 12-Module 02-Lesson 03_Searching and Sorting/01. Binary Search-0VN5iwEyq4c.pt-BR.vtt 2.01 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/10. Problems in the Data -oWu4UDkPmj8.zh-CN.vtt 2.01 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.ja.vtt 2.01 KB
Part 16-Module 03-Lesson 01_Basic SQL/40. NOT Operator-dSQF87oW8a0.zh-CN.vtt 2.01 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.ar.vtt 2.01 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.en-US.vtt 2 KB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.ar.vtt 2 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-CvTXyvw7QLc.pt-BR.vtt 2 KB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.en-US.vtt 2 KB
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-IMWsjjIeOrY.pt-BR.vtt 2 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -zWNcZ-7k7Tw.zh-CN.vtt 2 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.pt-BR.vtt 2 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.en.vtt 2 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/13. Tracking Down the Remaining Problems-Xblj5rT9i0M.en.vtt 2 KB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.en.vtt 2 KB
Part 11-Module 01-Lesson 12_Feature Selection/13. Overfitting by Eye-sJgPnuiHrs8.zh-CN.vtt 2 KB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.en.vtt 2 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.en.vtt 2 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-61sZUjEPzt0.zh-CN.vtt 2 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.ar.vtt 2 KB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.th.vtt 2 KB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.pt-BR.vtt 2 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/28. Improving Plots and Sharing Findings-anglRHbmsfw.zh-CN.vtt 2 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.ar.vtt 2 KB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.pt-BR.vtt 2 KB
Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.ar.vtt 2 KB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.ar.vtt 2 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.pt-BR.vtt 2 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.en.vtt 2 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/41. Types of Designs-IcrYt7Tzccg.zh-CN.vtt 2 KB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.en.vtt 2 KB
Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.ar.vtt 2 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.es.vtt 2 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.es.vtt 2 KB
Part 12-Module 02-Lesson 05_Trees/08. Search and Delete-KbL-HK3ztX8.pt-BR.vtt 2 KB
Part 11-Module 01-Lesson 16_Tying It All Together/04. Outro-VCNcNnZ6V_s.zh-CN.vtt 2 KB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.ar.vtt 2 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/22. Variability Example-kTXI_wnTbVk.en.vtt 2 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.es.vtt 1.99 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.ja.vtt 1.99 KB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.en.vtt 1.99 KB
Part 12-Module 02-Lesson 02_List-Based Collections/09. Stacks Details-HpaVHzDeZC4.zh-CN.vtt 1.99 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.pt-BR.vtt 1.99 KB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.it.vtt 1.99 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/18. Multicollinearity VIFs-uiF3UcDWwPI.en.vtt 1.99 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.ar.vtt 1.99 KB
Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.pt-BR.vtt 1.99 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.es-MX.vtt 1.99 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.ar.vtt 1.99 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.zh-CN.vtt 1.99 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.en-US.vtt 1.99 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.en.vtt 1.99 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/24. Many Variables-okzOTH15r3Y.zh-CN.vtt 1.99 KB
Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.en-US.vtt 1.99 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.pt-BR.vtt 1.99 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.pt-BR.vtt 1.99 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.pt-BR.vtt 1.99 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/02. Purpose-7F7cMCTcyhM.en.vtt 1.99 KB
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8xFV-I4VqZ0.pt-BR.vtt 1.99 KB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.pt-BR.vtt 1.99 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.en.vtt 1.99 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/01. Interview Introduction-dRsHYt1Lddc.pt-BR.vtt 1.99 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.pt-BR.vtt 1.99 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.pt-BR.vtt 1.99 KB
Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.en.vtt 1.99 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.en.vtt 1.99 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.ar.vtt 1.98 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.zh-CN.vtt 1.98 KB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.en-US.vtt 1.98 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro-8y2JZ2gEl1k.pt-BR.vtt 1.98 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/01. Intro-jOhaqX_9oy8.pt-BR.vtt 1.98 KB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.ar.vtt 1.98 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.zh-CN.vtt 1.98 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.ar.vtt 1.98 KB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.pt-BR.vtt 1.98 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/03. Developer Tools and Console-C2Ob9vkpQ7g.zh-CN.vtt 1.98 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.pt-BR.vtt 1.98 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.pt-BR.vtt 1.98 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt 1.98 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt 1.98 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.pt-BR.vtt 1.98 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.ar.vtt 1.98 KB
Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.pt-BR.vtt 1.98 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-0XM5ILuCg1k.zh-CN.vtt 1.98 KB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.ar.vtt 1.98 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.zh-CN.vtt 1.98 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.zh-CN.vtt 1.98 KB
Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.pt-BR.vtt 1.98 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/10. DataFrame Vectorized Operations-xbtnAlV0ZSA.zh-CN.vtt 1.98 KB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-g_V6OCICUUc.zh-CN.vtt 1.98 KB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.en.vtt 1.98 KB
Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ja.vtt 1.98 KB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.es-ES.vtt 1.98 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.pt-BR.vtt 1.97 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/09. Unit of Analysis vs. Diversion Example-vuu3BY7X9ps.zh-CN.vtt 1.97 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.ar.vtt 1.97 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.pt-BR.vtt 1.97 KB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.pt-BR.vtt 1.97 KB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.en.vtt 1.97 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ar.vtt 1.97 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.en.vtt 1.97 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-plnMY4iATyU.en.vtt 1.97 KB
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Part 05-Module 01-Lesson 03_Data in More Complex Formats/16. Beginning to Build Our http Requests-ojd7xXOd_64.en.vtt 1.96 KB
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Part 11-Module 01-Lesson 03_SVM/19. Kernel Trick-3Xw6FKYP7e4.zh-CN.vtt 1.96 KB
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-7kOZs5PLtqs.en.vtt 1.95 KB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.en.vtt 1.95 KB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.pt-BR.vtt 1.95 KB
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt 1.95 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/05. Resume Reflection-8Cj_tCp8mls.es-MX.vtt 1.95 KB
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Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.en.vtt 1.95 KB
Part 14-Module 01-Lesson 05_Analyzing Results/12. Multiple Metrics Introduction-dw0UylGwPe8.zh-CN.vtt 1.95 KB
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Part 13-Module 01-Lesson 04_Design Principles/14. Common and Less Common Charts on plot.ly-V9xxdiwJtWk.zh-CN.vtt 1.95 KB
Part 15-Module 01-Lesson 02_Design Principles/06. Gráficos Comuns e Menos Comuns no plot.ly-V9xxdiwJtWk.zh-CN.vtt 1.95 KB
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Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.pt-BR.vtt 1.95 KB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.pt-BR.vtt 1.95 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-OzPNbN4L_L0.zh-CN.vtt 1.95 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.pt-BR.vtt 1.94 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.ar.vtt 1.94 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.ar.vtt 1.94 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.ar.vtt 1.94 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.es.vtt 1.94 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.es.vtt 1.94 KB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.ar.vtt 1.94 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-7PyV7HxpSYA.zh-CN.vtt 1.94 KB
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.zh-CN.vtt 1.94 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.th.vtt 1.94 KB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.ar.vtt 1.94 KB
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.en.vtt 1.94 KB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.en.vtt 1.94 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-XZNKM3xMZNY.zh-CN.vtt 1.94 KB
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Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small-9ftDJRsfEUI.pt-BR.vtt 1.94 KB
Part 21-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.zh-CN.vtt 1.94 KB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.ja.vtt 1.94 KB
Part 11-Module 01-Lesson 13_PCA/38. Selecting Principal Components-IwcoGtFuYSo.zh-CN.vtt 1.94 KB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.en.vtt 1.94 KB
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Part 13-Module 01-Lesson 04_Design Principles/40. Lie Factor-jkR2kIJrvBM.zh-CN.vtt 1.94 KB
Part 18-Module 02-Lesson 01_Gathering Data/01. Introduction-XtJN72lBo94.en.vtt 1.94 KB
Part 05-Module 01-Lesson 05_Data Quality/02. What is Data Cleaning-dzqOwmxK3j4.ar.vtt 1.94 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/01. Intro to MongoDB-GfK7GW3V-W0.zh-CN.vtt 1.94 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/05. Elevator Pitch-0QtgTG49E9I.pt-BR.vtt 1.94 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.en.vtt 1.94 KB
Part 13-Module 01-Lesson 04_Design Principles/20. Negative Space-3toURbAUt9s.ar.vtt 1.94 KB
Part 13-Module 01-Lesson 05_Dimple.js/05. A Simple HTTP Server-h8Fa24E_I5s.en.vtt 1.94 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.es.vtt 1.94 KB
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Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.ar.vtt 1.94 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.pt-BR.vtt 1.93 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.pt-BR.vtt 1.93 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.ar.vtt 1.93 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/11. Which Tests Need Further Review-LlPsmQx5y50.zh-CN.vtt 1.93 KB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.en.vtt 1.93 KB
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Part 05-Module 02-Lesson 05_Deeper into SQL/02. Normalized Design Part One-LQq5F77ANiY.en.vtt 1.93 KB
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Part 12-Module 02-Lesson 02_List-Based Collections/05. Linked Lists-zxkpZrozDUk.zh-CN.vtt 1.93 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.en.vtt 1.93 KB
Part 19-Module 01-Lesson 02_Design/07. Chart Junk-3BTBEYOG2o8.zh-CN.vtt 1.93 KB
Part 21-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.zh-CN.vtt 1.93 KB
Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.ar.vtt 1.93 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.ar.vtt 1.93 KB
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Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-O0zo3-NtBSI.zh-CN.vtt 1.92 KB
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Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.en.vtt 1.92 KB
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Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.ar.vtt 1.92 KB
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Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.en.vtt 1.92 KB
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Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.zh-CN.vtt 1.92 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/15. Potential Problems-lGwB6YRThbI.zh-CN.vtt 1.92 KB
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python-KS6cKoKe8ms.en.vtt 1.92 KB
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Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.ar.vtt 1.92 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.pt-BR.vtt 1.92 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.ar.vtt 1.92 KB
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.pt-BR.vtt 1.92 KB
Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.pt-BR.vtt 1.92 KB
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Part 13-Module 01-Lesson 02_D3 Building Blocks/17. -NXGcCf1KCt4.zh-CN.vtt 1.92 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.pt-BR.vtt 1.92 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.en.vtt 1.92 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.en.vtt 1.91 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.en.vtt 1.91 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.ar.vtt 1.91 KB
Part 09-Module 01-Lesson 03_Explore One Variable/23. Add a Scaling Layer-SsNYXdi3q-I.zh-CN.vtt 1.91 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-S3f9BoG9TYA.zh-CN.vtt 1.91 KB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.ar.vtt 1.91 KB
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.en.vtt 1.91 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.en.vtt 1.91 KB
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Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.en.vtt 1.91 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-lVLgiRRhFpQ.zh-CN.vtt 1.91 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.ar.vtt 1.9 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.pt-BR.vtt 1.9 KB
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.pt-BR.vtt 1.9 KB
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Part 21-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.zh-CN.vtt 1.9 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.ar.vtt 1.9 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.en.vtt 1.9 KB
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Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.ar.vtt 1.89 KB
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Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.en.vtt 1.89 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.pt-BR.vtt 1.89 KB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.en.vtt 1.89 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.en.vtt 1.89 KB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.ja.vtt 1.89 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-CN.vtt 1.89 KB
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Part 01-Module 01-Lesson 01_Nanodegree Orientation/12. Final Tips-1ZVBvM54hQw.zh-CN.vtt 1.89 KB
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Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.ar.vtt 1.89 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.en.vtt 1.89 KB
Part 12-Module 01-Lesson 03_Interview Fails/02. Interviewing Fails Mike Wales-OGXRmzBglI4.zh-CN.vtt 1.89 KB
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Part 13-Module 01-Lesson 08_Animation and Interaction/11. Drawing a Map from SVG Paths-WGD8AWQg9dE.zh-CN.vtt 1.89 KB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.en.vtt 1.89 KB
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Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.ja.vtt 1.88 KB
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Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.ar.vtt 1.88 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.ja.vtt 1.88 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.pt-BR.vtt 1.88 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/39. Update the Title-ut83yNUYLmc.zh-CN.vtt 1.88 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.en.vtt 1.88 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-WZRsqdNrC1A.zh-CN.vtt 1.88 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/04. XML in Practice-4xsz7OkDJgM.zh-CN.vtt 1.88 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.pt-BR.vtt 1.88 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.ar.vtt 1.88 KB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.ar.vtt 1.88 KB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.pt-BR.vtt 1.88 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.ar.vtt 1.88 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.pt-BR.vtt 1.88 KB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.ar.vtt 1.88 KB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.pt-BR.vtt 1.88 KB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.ar.vtt 1.88 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.pt-BR.vtt 1.88 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-HTuI3iFzOdU.en.vtt 1.88 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.pt-BR.vtt 1.88 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.ar.vtt 1.88 KB
Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.pt-BR.vtt 1.88 KB
Part 17-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.pt-BR.vtt 1.88 KB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.en.vtt 1.88 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-GLQJukg-0fQ.en.vtt 1.88 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/05. Tabular Formats-5Vq530Lijb0.zh-CN.vtt 1.88 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.ja.vtt 1.88 KB
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Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.en.vtt 1.88 KB
Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.pt-BR.vtt 1.87 KB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-bcwFahJsww0.en.vtt 1.87 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/12. What's a DB-API-06LsRU4pmkA.en.vtt 1.87 KB
Part 07-Module 01-Lesson 01_GitHub Review/06. Quick Fixes-Lb9e2KemR6I.zh-CN.vtt 1.87 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.ar.vtt 1.87 KB
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-OGK9SHt8SWg.zh-CN.vtt 1.87 KB
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-FT0dM2um34E.zh-CN.vtt 1.87 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.pt-BR.vtt 1.87 KB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.pt-BR.vtt 1.87 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-9na_mOWP7pw.es.vtt 1.87 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.pt-BR.vtt 1.87 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.ja.vtt 1.87 KB
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.ar.vtt 1.87 KB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.zh-CN.vtt 1.87 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.pt-BR.vtt 1.87 KB
Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.ar.vtt 1.87 KB
Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.ar.vtt 1.87 KB
Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.ar.vtt 1.87 KB
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Part 11-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.ar.vtt 1.87 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/08. Map Distortions-xL5xVEuLuNE.zh-CN.vtt 1.87 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.en.vtt 1.87 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.en.vtt 1.87 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-KYAUEz-50-Q.zh-CN.vtt 1.87 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-KYAUEz-50-Q.zh-CN.vtt 1.87 KB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-djTM5fADIVs.pt-BR.vtt 1.87 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.it.vtt 1.87 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Operator-3vLGEuXAAvA.zh-CN.vtt 1.87 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.pt-BR.vtt 1.87 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.en.vtt 1.86 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-jKZAcZw9xLA.zh-CN.vtt 1.86 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.zh-CN.vtt 1.86 KB
Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.ar.vtt 1.86 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.en.vtt 1.86 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.en.vtt 1.86 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/15. Different Bin Sizes-_wOXWBZkL58.zh-CN.vtt 1.86 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/22. Comparing the Two Student Groups-eM82u21V7AM.zh-CN.vtt 1.86 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy--gJJmckPBAg.pt-BR.vtt 1.86 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.en.vtt 1.86 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.en-US.vtt 1.86 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.pt-BR.vtt 1.86 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-j0qfuunqym8.zh-CN.vtt 1.86 KB
Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.pt-BR.vtt 1.86 KB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.ar.vtt 1.86 KB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.pt-BR.vtt 1.86 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/11. How Do I Find Time for My Nanodegree Program-d-VfUw7wNEQ.zh-CN.vtt 1.86 KB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.ar.vtt 1.86 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.bg.vtt 1.86 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.en.vtt 1.86 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.pt-BR.vtt 1.86 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/14. Anscombe’s Quartet-Ftp3mmItV-k.en.vtt 1.86 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Anscombe’s Quartet-Ftp3mmItV-k.en.vtt 1.86 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.en.vtt 1.86 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.en.vtt 1.86 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.en.vtt 1.86 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt 1.86 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt 1.86 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.pt-BR.vtt 1.86 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.ja.vtt 1.86 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.ar.vtt 1.85 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.ja.vtt 1.85 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.en.vtt 1.85 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.ar.vtt 1.85 KB
Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.pt-BR.vtt 1.85 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-zovzbp_Rpu4.zh-CN.vtt 1.85 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-DlDQLxYRB4w.zh-CN.vtt 1.85 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.pt-BR.vtt 1.85 KB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.pt-BR.vtt 1.85 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.es-ES.vtt 1.85 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.es.vtt 1.85 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.es.vtt 1.85 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-CSVf96g0XGM.zh-CN.vtt 1.85 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.ar.vtt 1.85 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.en.vtt 1.85 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.ar.vtt 1.85 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.en.vtt 1.85 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.ar.vtt 1.85 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.pt-BR.vtt 1.85 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.pt-BR.vtt 1.84 KB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.pt-BR.vtt 1.84 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.th.vtt 1.84 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.pt-BR.vtt 1.84 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.pt-BR.vtt 1.84 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/16. Pandas groupby()-w3D0no7E8uw.zh-CN.vtt 1.84 KB
Part 09-Module 01-Lesson 03_Explore One Variable/15. Omitting NA Observations-SdYtgaZ5riY.zh-CN.vtt 1.84 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.en.vtt 1.84 KB
Part 09-Module 01-Lesson 01_What is EDA/02. Go Exploring-dias-YUpewk.zh-CN.vtt 1.84 KB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.en.vtt 1.84 KB
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Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.en-US.vtt 1.84 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.ar.vtt 1.84 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.ar.vtt 1.84 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.pt-BR.vtt 1.84 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.ar.vtt 1.84 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.ar.vtt 1.84 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.pt-BR.vtt 1.84 KB
Part 18-Module 03-Lesson 01_Assessing Data/01. Introduction-4U3nFMf2KEs.zh-CN.vtt 1.84 KB
Part 05-Module 02-Lesson 01_Data and Tables/01. Intro to SQL for Data Analysis-CU4igXr9xTw.zh-CN.vtt 1.84 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/07. Format-Xlqoq-SoJso.es-MX.vtt 1.84 KB
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-aZqYc7v8BK4.zh-CN.vtt 1.84 KB
Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.en.vtt 1.84 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.en.vtt 1.83 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.ar.vtt 1.83 KB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.pt-BR.vtt 1.83 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.pt-BR.vtt 1.83 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.pt-BR.vtt 1.83 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/01. Welcome to Evaluation Metrics Lesson-IHuFWRM9f9Q.ar.vtt 1.83 KB
Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.en.vtt 1.83 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.en.vtt 1.83 KB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.en.vtt 1.83 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.pt-BR.vtt 1.83 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-Hans.vtt 1.83 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-qyyAtT9vgr4.zh-Hans.vtt 1.83 KB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_afLozDIcLw.pt-BR.vtt 1.83 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.en.vtt 1.83 KB
Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.pt-BR.vtt 1.83 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/02. Sampling To Distributions To Confidence Intervals-QYMLkDToigc.zh-CN.vtt 1.83 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.ar.vtt 1.83 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.pt-BR.vtt 1.83 KB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.en.vtt 1.83 KB
Part 16-Module 03-Lesson 01_Basic SQL/21. Order By Part II-XQCjREdOqwE.zh-CN.vtt 1.83 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.ar.vtt 1.83 KB
Part 19-Module 01-Lesson 02_Design/19. Same Data Different Stories-jSSnkz3QT5Y.en.vtt 1.83 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.en.vtt 1.82 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.en.vtt 1.82 KB
Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.ar.vtt 1.82 KB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.ja.vtt 1.82 KB
Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.en-US.vtt 1.82 KB
Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.ar.vtt 1.82 KB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.en.vtt 1.82 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.en.vtt 1.82 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.en.vtt 1.82 KB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.ja.vtt 1.82 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.ar.vtt 1.82 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/26. Notation for the Mean-3EF15AoRxyM.zh-CN.vtt 1.82 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.en.vtt 1.82 KB
Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.en.vtt 1.82 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.en.vtt 1.82 KB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.pt-BR.vtt 1.82 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.ar.vtt 1.82 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.pt-BR.vtt 1.82 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.pt-BR.vtt 1.82 KB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.pt-BR.vtt 1.82 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.pt-BR.vtt 1.82 KB
Part 06-Module 01-Lesson 03_Analyzing Data/07. Aggregation Operators 2-UZMklqP5-p4.zh-CN.vtt 1.82 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.pt-BR.vtt 1.82 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.ar.vtt 1.82 KB
Part 11-Module 01-Lesson 04_Decision Trees/08. Coding A Decision Tree-cxV6OAxCfIQ.zh-CN.vtt 1.82 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.en.vtt 1.82 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.en.vtt 1.82 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.pt-BR.vtt 1.82 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.en.vtt 1.82 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/02. What's Ahead-ggbCydfI1JM.zh-CN.vtt 1.82 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.pt-BR.vtt 1.82 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.en.vtt 1.82 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.en.vtt 1.82 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.en.vtt 1.82 KB
Part 11-Module 01-Lesson 02_Naive Bayes/30. Bayes Rule Diagram-LIQrs3dviIs.zh-CN.vtt 1.81 KB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.pt-BR.vtt 1.81 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.ar.vtt 1.81 KB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.en.vtt 1.81 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.pt-BR.vtt 1.81 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.en.vtt 1.81 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.pt-BR.vtt 1.81 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.pt-BR.vtt 1.81 KB
Part 09-Module 01-Lesson 03_Explore One Variable/12. Limiting the Axes-1W3QAzrybMk.zh-CN.vtt 1.81 KB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.ar.vtt 1.81 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/23. Connecting Errors and P-Values-hFNjd5l9CLs.zh-CN.vtt 1.81 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.pt-BR.vtt 1.81 KB
Part 21-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.zh-CN.vtt 1.81 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/06. The Rise of Diamonds-MD9RIDRVc-A.zh-CN.vtt 1.81 KB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.pt-BR.vtt 1.81 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.pt-BR.vtt 1.81 KB
Part 11-Module 01-Lesson 04_Decision Trees/33. Bias-Variance Dilemma-W5uUYnSHDhM.zh-CN.vtt 1.81 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.ar.vtt 1.81 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.pt-BR.vtt 1.81 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.pt-BR.vtt 1.81 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/22. Decomposing Visualizations-iJ8t2FsPW4c.zh-CN.vtt 1.81 KB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.pt-BR.vtt 1.81 KB
Part 16-Module 03-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.pt-BR.vtt 1.81 KB
Part 08-Module 02-Lesson 01_Refine Your Entry-Level Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt 1.81 KB
Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt 1.81 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.es-MX.vtt 1.81 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.ar.vtt 1.81 KB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.th.vtt 1.81 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.ar.vtt 1.81 KB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.en.vtt 1.8 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/21. Rankings of Visual Encodings-ycsXqX7T80Y.zh-CN.vtt 1.8 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/08. Rankings of Visual Encodings - Data Visualization and D3.js-ycsXqX7T80Y.zh-CN.vtt 1.8 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.pt-BR.vtt 1.8 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/21. Splitting out Passing Students -Vf-EK6vg6Uc.zh-CN.vtt 1.8 KB
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.zh-CN.vtt 1.8 KB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.pt-BR.vtt 1.8 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-pn3MunHovMc.zh-CN.vtt 1.8 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.pt-BR.vtt 1.8 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.en.vtt 1.8 KB
Part 09-Module 01-Lesson 03_Explore One Variable/18. Labeling Plots-llvIDIu3Sw8.zh-CN.vtt 1.8 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.pt-BR.vtt 1.8 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.pt-BR.vtt 1.8 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.zh-CN.vtt 1.8 KB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.pt-BR.vtt 1.8 KB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.en.vtt 1.8 KB
Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.ar.vtt 1.8 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.ar.vtt 1.8 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.en.vtt 1.8 KB
Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.pt-BR.vtt 1.8 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.en.vtt 1.8 KB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.pt-BR.vtt 1.79 KB
Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.pt-BR.vtt 1.79 KB
Part 19-Module 01-Lesson 02_Design/18. Tell A Story-_IdOUEhjVGI.zh-CN.vtt 1.79 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/04. Introduction to Hashing-8yik3RlDFgM.zh-CN.vtt 1.79 KB
Part 11-Module 01-Lesson 16_Tying It All Together/01. Introduction-8tm1144C4T0.zh-CN.vtt 1.79 KB
Part 16-Module 03-Lesson 01_Basic SQL/18. ORDER BY Statement-wqj2As31LqI.zh-CN.vtt 1.79 KB
Part 18-Module 04-Lesson 01_Cleaning Data/01. Introduction -rkRn1Nh-6lg.en.vtt 1.79 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.en.vtt 1.79 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.ar.vtt 1.79 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.es-ES.vtt 1.79 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.en.vtt 1.79 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.ar.vtt 1.79 KB
Part 16-Module 03-Lesson 01_Basic SQL/30. Arithmetic Operators-fgcJdiNECxI.zh-CN.vtt 1.79 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.ar.vtt 1.79 KB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.ar.vtt 1.79 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.en.vtt 1.79 KB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.en.vtt 1.79 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.pt-BR.vtt 1.79 KB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.pt-BR.vtt 1.79 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.zh-CN.vtt 1.79 KB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.pt-BR.vtt 1.79 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-2DwKMiFjGPE.ja.vtt 1.79 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.pt-BR.vtt 1.79 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.zh-CN.vtt 1.79 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.pt-BR.vtt 1.79 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.pt-BR.vtt 1.79 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-lWjaCJazJE0.zh-CN.vtt 1.79 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.ar.vtt 1.79 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.ar.vtt 1.79 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.pt-BR.vtt 1.79 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/04. Time When You Showed Initiative-29mkriaGT0E.zh-CN.vtt 1.79 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/05. Confidence Interval for a Difference In Means-8hrWGzjyhck.zh-CN.vtt 1.79 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.ar.vtt 1.79 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.en.vtt 1.78 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.pt-BR.vtt 1.78 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.es.vtt 1.78 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.pt-BR.vtt 1.78 KB
Part 17-Module 01-Lesson 14_Regression/15. Fitting A Regression Line In Python-0CiMDbEUeS4.zh-CN.vtt 1.78 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.ar.vtt 1.78 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/31. Dependent Samples-kcTh3hJ1XCw.zh-CN.vtt 1.78 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/16. Subqueries-YWZ-bgnZWaM.zh-CN.vtt 1.78 KB
Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.pt-BR.vtt 1.78 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/12. Which Distribution-tTb1k27rhgI.zh-CN.vtt 1.78 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.ja.vtt 1.78 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.es.vtt 1.78 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.es.vtt 1.78 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.ar.vtt 1.78 KB
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.th.vtt 1.78 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.pt-BR.vtt 1.78 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-f7vNKm0Zci0.zh-CN.vtt 1.78 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.pt-BR.vtt 1.78 KB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-hxxa0KAkB1o.zh-CN.vtt 1.78 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.en.vtt 1.78 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.pt-BR.vtt 1.78 KB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.en.vtt 1.78 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.zh-CN.vtt 1.78 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.en.vtt 1.78 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.en.vtt 1.78 KB
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-7JS9PPQ6cN4.pt-BR.vtt 1.78 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.pt-BR.vtt 1.78 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.ja.vtt 1.78 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.pt-BR.vtt 1.78 KB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.en.vtt 1.77 KB
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Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.en.vtt 1.77 KB
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Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.en.vtt 1.75 KB
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Part 17-Module 01-Lesson 11_Confidence Intervals/12. Other Language Associated With Confidence Intervals-9KYVRx7-llg.zh-CN.vtt 1.75 KB
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Part 12-Module 02-Lesson 05_Trees/02. Tree Basics-oaxLPzaXRDc.zh-CN.vtt 1.75 KB
Part 13-Module 01-Lesson 07_Narrative Structures/30. Thinking with Venn Diagrams-C1aHeMSeIdk.zh-CN.vtt 1.75 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.ar.vtt 1.75 KB
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Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -_mge9UU-gpQ.zh-CN.vtt 1.74 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.pt-BR.vtt 1.74 KB
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.en.vtt 1.74 KB
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Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.ar.vtt 1.74 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.ko.vtt 1.73 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.pt-BR.vtt 1.73 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.pt-BR.vtt 1.73 KB
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Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.pt-BR.vtt 1.72 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.en.vtt 1.72 KB
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Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.es-ES.vtt 1.72 KB
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Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.en-US.vtt 1.72 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.en.vtt 1.72 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.en.vtt 1.72 KB
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Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.en.vtt 1.72 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.pt-BR.vtt 1.72 KB
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Part 13-Module 01-Lesson 05_Dimple.js/11. Chart Layout and Group Tags--2yj49s7v5w.zh-CN.vtt 1.72 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/24. How Does Number of Page Views Vary-tfhsgVCX2Ao.zh-CN.vtt 1.72 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.ar.vtt 1.72 KB
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Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.pt-BR.vtt 1.72 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/22. Having-D4gmN0vnk58.en.vtt 1.72 KB
Part 17-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.zh-CN.vtt 1.72 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.ar.vtt 1.72 KB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.en.vtt 1.72 KB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.en.vtt 1.71 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.pt-BR.vtt 1.71 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.en.vtt 1.71 KB
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.en.vtt 1.71 KB
Part 17-Module 01-Lesson 16_Logistic Regression/06. Interpreting Results-UPOxxbKu6CQ.zh-CN.vtt 1.71 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.en.vtt 1.71 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.en.vtt 1.71 KB
Part 11-Module 01-Lesson 08_Outliers/04. Outlier DetectionRemoval Algorithm-hGKY6BAqJ6o.zh-CN.vtt 1.71 KB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.pt-BR.vtt 1.71 KB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.pt-BR.vtt 1.71 KB
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Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.en.vtt 1.71 KB
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Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.ar.vtt 1.71 KB
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Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.pt-BR.vtt 1.71 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.pt-BR.vtt 1.71 KB
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Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.en.vtt 1.71 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/01. Welcome!-KJT4Z0xpHns.zh-CN.vtt 1.71 KB
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Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.en.vtt 1.71 KB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.pt-BR.vtt 1.71 KB
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Part 08-Module 02-Lesson 02_Refine Your Career Change Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt 1.71 KB
Part 08-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume/04. Describe Your Work Experiences-B1LED4txinI.zh-CN.vtt 1.71 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.zh-CN.vtt 1.7 KB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.ar.vtt 1.7 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.pt-BR.vtt 1.7 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-VFS9mGdkU-M.pt-BR.vtt 1.7 KB
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Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.en.vtt 1.7 KB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.pt-BR.vtt 1.7 KB
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-t2Nq3MFK_pg.zh-CN.vtt 1.7 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.en.vtt 1.7 KB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.en.vtt 1.7 KB
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Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.pt-BR.vtt 1.7 KB
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Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/02. Data Overview-u_qB4w4kL1o.zh-CN.vtt 1.7 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.pt-BR.vtt 1.7 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.en.vtt 1.7 KB
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Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.pt-BR.vtt 1.7 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/01. Intro-8y2JZ2gEl1k.zh-CN.vtt 1.7 KB
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Part 11-Module 01-Lesson 07_Regressions/30. R Squared Metric for Regression-yDJEP-XSWdU.zh-CN.vtt 1.7 KB
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Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.ar.vtt 1.69 KB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.pt-BR.vtt 1.69 KB
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.ar.vtt 1.69 KB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.th.vtt 1.69 KB
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Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -z-mXs7Rl-Ys.zh-CN.vtt 1.69 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.pt-BR.vtt 1.69 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-8HFOaRdDpek.zh-CN.vtt 1.69 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.pt-BR.vtt 1.69 KB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.en.vtt 1.69 KB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-wl3gjMMrYwM.zh-CN.vtt 1.69 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-8HFOaRdDpek.zh-CN.vtt 1.69 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.en.vtt 1.69 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.en.vtt 1.69 KB
Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.en.vtt 1.69 KB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.en.vtt 1.69 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-ErwocwQVgYE.zh-CN.vtt 1.69 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/14. The Central Limit Theorem-ag3TB5UGu_g.zh-CN.vtt 1.69 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/01. Introduction-0ydaJl3wCkU.zh-CN.vtt 1.69 KB
Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.ar.vtt 1.69 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.es-ES.vtt 1.69 KB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.es-ES.vtt 1.69 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-h-YgETh80h4.zh-CN.vtt 1.68 KB
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-o75xNa_jwvg.zh-CN.vtt 1.68 KB
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.ar.vtt 1.68 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.en.vtt 1.68 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-9piyE5in7YE.zh-CN.vtt 1.68 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.en.vtt 1.68 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.ar.vtt 1.68 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.ja.vtt 1.68 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.ar.vtt 1.68 KB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.ja.vtt 1.68 KB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.en.vtt 1.68 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.pt-BR.vtt 1.68 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.ar.vtt 1.68 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.hr.vtt 1.68 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.en-US.vtt 1.68 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.ar.vtt 1.68 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/01. Introduction to Data Wrangling-4cFsT9KBRs8.zh-CN.vtt 1.68 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.ar.vtt 1.68 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.ar.vtt 1.68 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/12. Caution with Class Selections-fP30uBJljNk.en.vtt 1.68 KB
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.ar.vtt 1.68 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.en.vtt 1.68 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.en.vtt 1.68 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.pt-BR.vtt 1.68 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.en.vtt 1.68 KB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.pt-BR.vtt 1.68 KB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.pt-BR.vtt 1.67 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.pt-BR.vtt 1.67 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.en.vtt 1.67 KB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.en.vtt 1.67 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-XoQr2hohdvI.zh-CN.vtt 1.67 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-CvB2qkSk1Zc.zh-CN.vtt 1.67 KB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.en.vtt 1.67 KB
Part 16-Module 03-Lesson 02_SQL Joins/13. Motivation for Other JOINs-3qdv1Ojc9Og.pt-BR.vtt 1.67 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-VUfaXWrr3oY.zh-CN.vtt 1.67 KB
Part 11-Module 01-Lesson 07_Regressions/32. Visualizing Regression-zQAHZhcsXoQ.zh-CN.vtt 1.67 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/08. Dummy Variables--QTgDd-fZuA.zh-CN.vtt 1.67 KB
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.en.vtt 1.67 KB
Part 13-Module 01-Lesson 04_Design Principles/29. Correcting Color-7vaHp4caWxw.zh-CN.vtt 1.67 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/28. Outlining the Update Function-k5ZZQ3ulwX4.en.vtt 1.67 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.ar.vtt 1.67 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.en.vtt 1.67 KB
Part 17-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.en.vtt 1.67 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.pt-BR.vtt 1.67 KB
Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.en.vtt 1.67 KB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.en.vtt 1.67 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.es.vtt 1.67 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.es.vtt 1.67 KB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.pt-BR.vtt 1.67 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.en.vtt 1.67 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.en.vtt 1.67 KB
Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.pt-BR.vtt 1.67 KB
Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.ja.vtt 1.66 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.en.vtt 1.66 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.pt-BR.vtt 1.66 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.pt-BR.vtt 1.66 KB
Part 16-Module 03-Lesson 02_SQL Joins/01. Introduction to JOINs-YvZ010GU-Ck.en.vtt 1.66 KB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.pt-BR.vtt 1.66 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.en.vtt 1.66 KB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.ja.vtt 1.66 KB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.en.vtt 1.66 KB
Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.en.vtt 1.66 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.en.vtt 1.66 KB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.en-US.vtt 1.66 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-QJxhBCWK6BQ.zh-CN.vtt 1.66 KB
Part 17-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.en.vtt 1.66 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/19. Pooled Standard Error-iub8yWiO84I.zh-CN.vtt 1.66 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/10. Traditional Confidence Interval Methods-DmZwYHuz2eM.en.vtt 1.66 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.en.vtt 1.66 KB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.pt-BR.vtt 1.66 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.pt-BR.vtt 1.66 KB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.pt-BR.vtt 1.66 KB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.en.vtt 1.66 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.ar.vtt 1.66 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/22. Bootstrapping-42j3YclcZ4Q.zh-CN.vtt 1.66 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.pt-BR.vtt 1.66 KB
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.pt-BR.vtt 1.65 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.en.vtt 1.65 KB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.en.vtt 1.65 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-sLEF-B1fkX8.zh-CN.vtt 1.65 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.ja.vtt 1.65 KB
Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.ar.vtt 1.65 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/11. Z-Table-hSAxcGBxbds.zh-CN.vtt 1.65 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.ar.vtt 1.65 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-t18YC5rLyWg.zh-CN.vtt 1.65 KB
Part 11-Module 01-Lesson 12_Feature Selection/10. Feature Selection in TfIdf Vectorizer-oZkDSuhBEkE.zh-CN.vtt 1.65 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/22. NEW D3 Scale Syntax-ba-Luz-Ip0Y.zh-CN.vtt 1.65 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.ar.vtt 1.65 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/09. Asking Questions-EvhIgrXtOao.zh-CN.vtt 1.65 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.ar.vtt 1.65 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.pt-BR.vtt 1.65 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.ar.vtt 1.65 KB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.pt-BR.vtt 1.65 KB
Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.ar.vtt 1.65 KB
Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.ar.vtt 1.65 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.en-US.vtt 1.65 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/24. Adjusting the Map Aesthetics-tc1Aai8e-w0.en.vtt 1.65 KB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.ar.vtt 1.64 KB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.pt-BR.vtt 1.64 KB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.pt-BR.vtt 1.64 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.pt-BR.vtt 1.64 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes-ODDruv2Qkdg.pt-BR.vtt 1.64 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/23. The Radius Scale-Rkrj1HjaMQM.en.vtt 1.64 KB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.pt-BR.vtt 1.64 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.en.vtt 1.64 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/16. Comparing Row to Previous Row-Z_x5ZJyDZog.zh-CN.vtt 1.64 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.th.vtt 1.64 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/12. One-Sample t-Test-QyjjSIvJ_F4.zh-CN.vtt 1.64 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.it.vtt 1.64 KB
Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.pt-BR.vtt 1.64 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/24. Are your Results Just Noise-LjuF5M6ymPA.zh-CN.vtt 1.64 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/09. Handling Attributes-YSEGZMBbxTk.zh-CN.vtt 1.64 KB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.en.vtt 1.64 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.zh-CN.vtt 1.64 KB
Part 09-Module 01-Lesson 01_What is EDA/04. Aude's Interest in Data-DDNSMG_RltY.zh-CN.vtt 1.64 KB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.pt-BR.vtt 1.64 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-tGHQsk1SGGU.zh-CN.vtt 1.64 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.en.vtt 1.64 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.ar.vtt 1.64 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.ar.vtt 1.64 KB
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.ar.vtt 1.64 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.pt-BR.vtt 1.64 KB
Part 21-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.zh-CN.vtt 1.64 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/20. When Does the CLT Not Work-uZGTVUEMfrU.en.vtt 1.63 KB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.en.vtt 1.63 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.ar.vtt 1.63 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.pt-BR.vtt 1.63 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/23. Measures of Center-eNoE9hSDxPA.en.vtt 1.63 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.pt-BR.vtt 1.63 KB
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Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.en.vtt 1.63 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.pt-BR.vtt 1.63 KB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.en.vtt 1.63 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.ar.vtt 1.63 KB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.en.vtt 1.63 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.ar.vtt 1.63 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.ar.vtt 1.63 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.ar.vtt 1.63 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.ar.vtt 1.63 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/01. Introduction-QXxtu_gdWQs.en.vtt 1.63 KB
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-S1yjJWWza7g.zh-CN.vtt 1.63 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.pt-BR.vtt 1.63 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/02. Introduction-QXxtu_gdWQs.en.vtt 1.63 KB
Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.en.vtt 1.63 KB
Part 05-Module 02-Lesson 03_Elements of SQL/09. SELECT Clauses-_bnZEnWWqXQ.zh-CN.vtt 1.63 KB
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.ar.vtt 1.63 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.pt-BR.vtt 1.63 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.pt-BR.vtt 1.63 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.pt-BR.vtt 1.63 KB
Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.ar.vtt 1.63 KB
Part 09-Module 01-Lesson 02_R Basics/05. Install RStudio on a Mac-buCEFFuLpYo.zh-CN.vtt 1.63 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.ja.vtt 1.63 KB
Part 11-Module 01-Lesson 12_Feature Selection/02. A New Enron Feature-m2-LkgEfLO0.zh-CN.vtt 1.63 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/21. Adding SVG Elements-Vx9n2qXwL6w.zh-CN.vtt 1.63 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip File 1-V7STsHoZ2gA.pt-BR.vtt 1.63 KB
Part 05-Module 01-Lesson 05_Data Quality/04. Sources of Dirty Data-h12MQ3d1Z1Y.zh-CN.vtt 1.62 KB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.pt-BR.vtt 1.62 KB
Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.pt-BR.vtt 1.62 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.ar.vtt 1.62 KB
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Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-pH51jLfGXe0.zh-CN.vtt 1.62 KB
Part 13-Module 01-Lesson 07_Narrative Structures/40. Creating Time and Attendance Scales-PgAp8ob4hIM.zh-CN.vtt 1.62 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.ar.vtt 1.62 KB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-M_8000Yz_DA.en.vtt 1.62 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.en.vtt 1.62 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.pt-BR.vtt 1.62 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.ar.vtt 1.62 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.en.vtt 1.62 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.pt-BR.vtt 1.62 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.pt-BR.vtt 1.62 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.pt-BR.vtt 1.62 KB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.pt-BR.vtt 1.62 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.en.vtt 1.62 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.pt-BR.vtt 1.62 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.en.vtt 1.62 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.ja.vtt 1.62 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.en.vtt 1.62 KB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.pt-BR.vtt 1.62 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/24. The Facebook Offering Animation-s7h2tH6z9Rg.en.vtt 1.62 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.pt-BR.vtt 1.62 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.ar.vtt 1.62 KB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.ja.vtt 1.62 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.pt-BR.vtt 1.62 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/08. Standardizing Data-a6oG3g7aKR4.zh-CN.vtt 1.62 KB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.zh-CN.vtt 1.62 KB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.ar.vtt 1.62 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/09. Standardizing Data-a6oG3g7aKR4.zh-CN.vtt 1.62 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.ar.vtt 1.62 KB
Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.ar.vtt 1.62 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.ja.vtt 1.61 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.pt-BR.vtt 1.61 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/06. Ethical Considerations for Diversion-Zf0XzYNsado.zh-CN.vtt 1.61 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.en.vtt 1.61 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.pt-BR.vtt 1.61 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.ja.vtt 1.61 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.zh-CN.vtt 1.61 KB
Part 12-Module 02-Lesson 02_List-Based Collections/02. Lists-KUQSgUMtyv0.zh-CN.vtt 1.61 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.en.vtt 1.61 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.es.vtt 1.61 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.en.vtt 1.61 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.en.vtt 1.61 KB
Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.ar.vtt 1.61 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.ar.vtt 1.61 KB
Part 14-Module 01-Lesson 05_Analyzing Results/14. Multiple Metrics Example 2-m0E26ndQBNo.zh-CN.vtt 1.61 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.pt-BR.vtt 1.61 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.zh-CN.vtt 1.61 KB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-sXeVydVAv7Q.zh-CN.vtt 1.61 KB
Part 03-Module 01-Lesson 20_L8 Estimation/19. Engagement Ratio-EdIcXVIYX88.zh-CN.vtt 1.61 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.pt-BR.vtt 1.61 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.ar.vtt 1.61 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.en.vtt 1.61 KB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.ar.vtt 1.61 KB
Part 09-Module 01-Lesson 01_What is EDA/09. Course Overview-W8N0aSMPff8.en.vtt 1.61 KB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.pt-BR.vtt 1.61 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.pt-BR.vtt 1.61 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.en.vtt 1.61 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.pt-BR.vtt 1.61 KB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.en.vtt 1.61 KB
Part 13-Module 01-Lesson 05_Dimple.js/06. Dimple Bar Chart Code Overview-vuxN6EC_gso.zh-CN.vtt 1.61 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.en.vtt 1.61 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.en.vtt 1.61 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.en.vtt 1.61 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/08. Infinitely Small-9ftDJRsfEUI.en.vtt 1.61 KB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.pt-BR.vtt 1.61 KB
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.hi.vtt 1.61 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.pt-BR.vtt 1.61 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/05. CREATE TABLE and Types-7DCw86WMpYo.zh-CN.vtt 1.6 KB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.en.vtt 1.6 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/01. Instructor Introduction Juno Lee-to8Pp3PCOZo.zh-CN.vtt 1.6 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.ar.vtt 1.6 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.ar.vtt 1.6 KB
Part 21-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.zh-CN.vtt 1.6 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.zh-CN.vtt 1.6 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.ja.vtt 1.6 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.ar.vtt 1.6 KB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.en.vtt 1.6 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.es.vtt 1.6 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.en.vtt 1.6 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.pt-BR.vtt 1.6 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.en.vtt 1.6 KB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.en.vtt 1.6 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.pt-BR.vtt 1.6 KB
Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.pt-BR.vtt 1.6 KB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.ar.vtt 1.6 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.zh-CN.vtt 1.6 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-0ezYH2ppmT0.zh-CN.vtt 1.6 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/32. What Happened-vD9iXeq3PKc.zh-CN.vtt 1.6 KB
Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.pt-BR.vtt 1.6 KB
Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.pt-BR.vtt 1.6 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.en.vtt 1.6 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/15. Who Has More Shoes-ODDruv2Qkdg.en.vtt 1.6 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.pt-BR.vtt 1.6 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.ja.vtt 1.6 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.en.vtt 1.6 KB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.ar.vtt 1.6 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.pt-BR.vtt 1.6 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/26. Use Measures of Center to Compare-KFK1L4hUW80.zh-CN.vtt 1.6 KB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.en.vtt 1.6 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.pt-BR.vtt 1.6 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.en.vtt 1.6 KB
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.th.vtt 1.6 KB
Part 21-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.zh-CN.vtt 1.6 KB
Part 12-Module 02-Lesson 05_Trees/16. Heapify-CAbDbiCfERY.zh-CN.vtt 1.6 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.zh-CN.vtt 1.59 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-N9VgCuxpb0I.zh-CN.vtt 1.59 KB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.ar.vtt 1.59 KB
Part 12-Module 02-Lesson 06_Graphs/04. Connectivity-4x6u2KtNDg4.zh-CN.vtt 1.59 KB
Part 16-Module 03-Lesson 01_Basic SQL/15. LIMIT Statement-cCPHNNhBgpQ.zh-CN.vtt 1.59 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/12. Variance Standard Deviation Final Points-vXUgp2375j4.zh-CN.vtt 1.59 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.en.vtt 1.59 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.es.vtt 1.59 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.es.vtt 1.59 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.en.vtt 1.59 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.en.vtt 1.59 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.ar.vtt 1.59 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/10. Overlaying Summaries with Raw Data-wqvEtUA0n-s.zh-CN.vtt 1.59 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/30. CASE Statements and Aggregations-asSXB6iD3z4.zh-CN.vtt 1.59 KB
Part 13-Module 01-Lesson 04_Design Principles/24. Redundant Encodings-RU3rI_pO8Rc.en.vtt 1.59 KB
Part 17-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.ja.vtt 1.59 KB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.ja.vtt 1.59 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.pt-BR.vtt 1.59 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.ar.vtt 1.59 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.es.vtt 1.59 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.pt-BR.vtt 1.59 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-4QMqg8izUac.zh-CN.vtt 1.59 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.ar.vtt 1.59 KB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.ja.vtt 1.59 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.zh-CN.vtt 1.59 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.ar.vtt 1.59 KB
Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.ja.vtt 1.59 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.ar.vtt 1.59 KB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.ar.vtt 1.59 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.zh-CN.vtt 1.59 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-CiS4rBbr6tw.zh-CN.vtt 1.59 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/03. Unit of Diversion Example-_-BxFJTBNMM.zh-CN.vtt 1.59 KB
Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.en.vtt 1.59 KB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.ar.vtt 1.59 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/01. Introduction to Data Visualization-MUZXLvBI2sw.zh-CN.vtt 1.59 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.en.vtt 1.59 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/01. Introduction to Data Visualization-MUZXLvBI2sw.zh-CN.vtt 1.59 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.pt-BR.vtt 1.58 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.pt-BR.vtt 1.58 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.en.vtt 1.58 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.ar.vtt 1.58 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.pt-BR.vtt 1.58 KB
Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.en.vtt 1.58 KB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.ar.vtt 1.58 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/29. Let's Make a Bar Chart-PlhGAjAZFhw.zh-CN.vtt 1.58 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.en.vtt 1.58 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.en.vtt 1.58 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.en.vtt 1.58 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.pt-BR.vtt 1.58 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.pt-BR.vtt 1.58 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.ar.vtt 1.58 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-9na_mOWP7pw.en.vtt 1.58 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-9na_mOWP7pw.en.vtt 1.58 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.ja.vtt 1.58 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.en.vtt 1.58 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.en.vtt 1.58 KB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.pt-BR.vtt 1.58 KB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.ar.vtt 1.58 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.pt-BR.vtt 1.58 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.pt-BR.vtt 1.58 KB
Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.en.vtt 1.58 KB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.pt-BR.vtt 1.58 KB
Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.en.vtt 1.58 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.en.vtt 1.58 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.en.vtt 1.58 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.pt-BR.vtt 1.58 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.en-US.vtt 1.58 KB
Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.en.vtt 1.58 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/07. Calculate Overall Completion Rate-zlopUR9utUY.zh-CN.vtt 1.58 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/08. Calculate Overall Completion Rate-zlopUR9utUY.zh-CN.vtt 1.58 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-TVN4JfSm144.en.vtt 1.58 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.ar.vtt 1.58 KB
Part 07-Module 01-Lesson 01_GitHub Review/01. Introduction-Vnj2VNQROtI.en.vtt 1.58 KB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.ja.vtt 1.58 KB
Part 11-Module 01-Lesson 12_Feature Selection/21. Feature Selection Mini-Project Video-sJzKx_FiMXA.zh-CN.vtt 1.58 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.en.vtt 1.57 KB
Part 13-Module 01-Lesson 07_Narrative Structures/32. From Dimple to D3-0yJzBWRQi5U.zh-CN.vtt 1.57 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.en.vtt 1.57 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.en.vtt 1.57 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/01. Choose Your own Algorithm-tpbHNLv-HT0.en.vtt 1.57 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.pt-BR.vtt 1.57 KB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.en.vtt 1.57 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.en.vtt 1.57 KB
Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.pt-BR.vtt 1.57 KB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.en.vtt 1.57 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.pt-BR.vtt 1.57 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.pt-BR.vtt 1.57 KB
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-eeV5K5HKVx4.zh-CN.vtt 1.57 KB
Part 09-Module 01-Lesson 03_Explore One Variable/28. Getting Logical-52o_ZtwFuXE.zh-CN.vtt 1.57 KB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.ar.vtt 1.57 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.pt-BR.vtt 1.57 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.en.vtt 1.57 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-MLGu66F25qU.en.vtt 1.57 KB
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Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.pt-BR.vtt 1.57 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.en.vtt 1.57 KB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.en.vtt 1.57 KB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.pt-BR.vtt 1.57 KB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.ar.vtt 1.57 KB
Part 18-Module 03-Lesson 01_Assessing Data/10. Assessing Vs Exploring V2 -hVFZ6jFKOso.en.vtt 1.57 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.pt-BR.vtt 1.57 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.pt-BR.vtt 1.57 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.pt-BR.vtt 1.57 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.pt-BR.vtt 1.57 KB
Part 18-Module 02-Lesson 01_Gathering Data/05. Source Files On Hand-PjP-EaeXTiY.zh-CN.vtt 1.57 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files from the Internet-UceKUJ07Bn8.zh-CN.vtt 1.57 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.pt-BR.vtt 1.56 KB
Part 12-Module 01-Lesson 05_Interview Practice/02. Describe your latest data project-wkWDrSBBtz0.en.vtt 1.56 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.pt-BR.vtt 1.56 KB
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.zh-CN.vtt 1.56 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.en.vtt 1.56 KB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.pt-BR.vtt 1.56 KB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.ko.vtt 1.56 KB
Part 09-Module 01-Lesson 02_R Basics/15. Data Munging-q_Ghc6VsDo0.en.vtt 1.56 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/09. Conditional Means-8oM8KjsntG8.zh-CN.vtt 1.56 KB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.pt-PT.vtt 1.56 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.ar.vtt 1.56 KB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.en.vtt 1.56 KB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.ar.vtt 1.56 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.en.vtt 1.56 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-VFS9mGdkU-M.en.vtt 1.56 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/09. Maps in D3-DAfs_MCYP0o.zh-CN.vtt 1.56 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.ar.vtt 1.56 KB
Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.en.vtt 1.56 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.pt-BR.vtt 1.56 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.pt-BR.vtt 1.56 KB
Part 09-Module 01-Lesson 03_Explore One Variable/09. Be Skeptical Outliers and Anomalies-kAisC2wRGBU.en.vtt 1.56 KB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.pt-BR.vtt 1.56 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-3pT4mwTqxoA.zh-CN.vtt 1.56 KB
Part 13-Module 01-Lesson 07_Narrative Structures/49. Orienting and Drawing the Axes-I9-ysMlq-Xc.zh-CN.vtt 1.56 KB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.pt-BR.vtt 1.56 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.pt-BR.vtt 1.56 KB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.pt-BR.vtt 1.56 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/14. Correct Interpretations of Confidence Intervals-IhYv_SlN7e8.pt-BR.vtt 1.56 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.pt-BR.vtt 1.55 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.en.vtt 1.55 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.es.vtt 1.55 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.es.vtt 1.55 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-hoVOT8qcQ7c.zh-CN.vtt 1.55 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.zh-CN.vtt 1.55 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.ar.vtt 1.55 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/17. Calculating Hourly Entries and Exits-_DBUiLAC_z8.zh-CN.vtt 1.55 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/27. Udacians' Facebook Friends - Mean-ljBJOXJTR9A.en.vtt 1.55 KB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.en.vtt 1.55 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.ar.vtt 1.55 KB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.ar.vtt 1.55 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.ar.vtt 1.55 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.en.vtt 1.55 KB
Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.pt-BR.vtt 1.55 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.es-ES.vtt 1.55 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.ar.vtt 1.55 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.ar.vtt 1.55 KB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.en.vtt 1.55 KB
Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.ar.vtt 1.55 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/26. Communicating Results Example-Ae_UOATWmDM.zh-CN.vtt 1.55 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.ar.vtt 1.55 KB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.ko.vtt 1.55 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/04. Prerequisites-0ANDJ8i_deE.zh-CN.vtt 1.55 KB
Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.en.vtt 1.55 KB
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-t0iflCpBUDA.zh-CN.vtt 1.55 KB
Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.pt-BR.vtt 1.55 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/27. Empirical Variability Bootstrapping-FvtAeWdzy4k.zh-CN.vtt 1.55 KB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.ar.vtt 1.55 KB
Part 05-Module 01-Lesson 05_Data Quality/13. Auditing Accuracy-mADDYP7ldl4.zh-CN.vtt 1.55 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.pt-BR.vtt 1.54 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/21. Duration vs. Exposure Example-993P7ivCrnQ.zh-CN.vtt 1.54 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.pt-BR.vtt 1.54 KB
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.th.vtt 1.54 KB
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-NXbR9GQbtnk.zh-CN.vtt 1.54 KB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.pt-BR.vtt 1.54 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.en.vtt 1.54 KB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.pt-BR.vtt 1.54 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/08. Darts-fSj1dwh7Kxc.zh-CN.vtt 1.54 KB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.en.vtt 1.54 KB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.pt-BR.vtt 1.54 KB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.pt-BR.vtt 1.54 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/06. 5 Number Summary to Variance-Ljhau0hrZ1g.en.vtt 1.54 KB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.pt-BR.vtt 1.54 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.pt-BR.vtt 1.54 KB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.ja.vtt 1.54 KB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.pt-BR.vtt 1.54 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.en.vtt 1.54 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.zh-CN.vtt 1.54 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-8_SBvU8NYak.zh-CN.vtt 1.54 KB
Part 05-Module 01-Lesson 05_Data Quality/16. Auditing Consistency-bCAkWxApvQM.zh-CN.vtt 1.54 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.en.vtt 1.54 KB
Part 13-Module 01-Lesson 07_Narrative Structures/05. The Difficulty of Data Visualization-xzo96P5BwSI.zh-CN.vtt 1.54 KB
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.ar.vtt 1.54 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.pt-BR.vtt 1.54 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.pt-BR.vtt 1.54 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.pt-BR.vtt 1.54 KB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.en.vtt 1.54 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.ar.vtt 1.54 KB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.ar.vtt 1.54 KB
Part 13-Module 01-Lesson 04_Design Principles/04. Chart Types-0a5oJR6TwAs.en.vtt 1.54 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/24. MM CLT-IAVgtiZLlOg.zh-CN.vtt 1.54 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.en.vtt 1.54 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.ar.vtt 1.54 KB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.en.vtt 1.54 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/08. Hierarchies with Trina-ys8Cn0o5gNI.zh-CN.vtt 1.54 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/03. Hierarchies with Trina-ys8Cn0o5gNI.zh-CN.vtt 1.54 KB
Part 03-Module 01-Lesson 20_L8 Estimation/20. Hypothesis Testing Song-ER5AITzr77g.zh-CN.vtt 1.53 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.ja.vtt 1.53 KB
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Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.pt-BR.vtt 1.53 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/21. Sampling Observations-PsRMReOqccg.zh-CN.vtt 1.53 KB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.ar.vtt 1.53 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.pt-BR.vtt 1.53 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.ar.vtt 1.53 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/35. Summary of the Update Function-IVmBlMgErzY.zh-CN.vtt 1.53 KB
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Part 17-Module 01-Lesson 14_Regression/04. Introduction to Linear Regression-RD4zbBvXDnM.zh-CN.vtt 1.53 KB
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Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.ar.vtt 1.53 KB
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Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.ar.vtt 1.53 KB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.pt-BR.vtt 1.53 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.pt-BR.vtt 1.53 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-0tcbCIrJGlM.pt-BR.vtt 1.53 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.pt-BR.vtt 1.53 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.pt-BR.vtt 1.53 KB
Part 13-Module 01-Lesson 04_Design Principles/08. Unemployment Line Plot-EbD9ufptNd0.en.vtt 1.53 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.ar.vtt 1.53 KB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.es-ES.vtt 1.53 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-_Z4d6-d-glM.zh-CN.vtt 1.52 KB
Part 12-Module 01-Lesson 05_Interview Practice/03. Free Throw Probability-pDELcPTP2BI.pt-BR.vtt 1.52 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-vasdN2Gol0M.ja.vtt 1.52 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-_Z4d6-d-glM.zh-CN.vtt 1.52 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.pt-BR.vtt 1.52 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.en-US.vtt 1.52 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.zh-CN.vtt 1.52 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.en-US.vtt 1.52 KB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.pt-BR.vtt 1.52 KB
Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.pt-BR.vtt 1.52 KB
Part 19-Module 01-Lesson 02_Design/14. Designing for Color Blindness-k4iTzS7t2U4.zh-CN.vtt 1.52 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.en.vtt 1.52 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.en.vtt 1.52 KB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.en.vtt 1.52 KB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.ar.vtt 1.52 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.en.vtt 1.52 KB
Part 11-Module 01-Lesson 13_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.zh-CN.vtt 1.52 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.en.vtt 1.52 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.pt-BR.vtt 1.52 KB
Part 18-Module 02-Lesson 01_Gathering Data/17. JSON Files In Python-8JdUknZP59Q.zh-CN.vtt 1.52 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations-q5PjL9GkVtM.en.vtt 1.52 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.ar.vtt 1.52 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-P6ZOr7JiMLk.zh-CN.vtt 1.52 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-MV_e0z9kFjM.zh-CN.vtt 1.52 KB
Part 12-Module 02-Lesson 02_List-Based Collections/01. Welcome to Collections-cZORvZq-tI0.zh-CN.vtt 1.52 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.pt-BR.vtt 1.52 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.en.vtt 1.52 KB
Part 11-Module 01-Lesson 02_Naive Bayes/04. Features and Labels Musical Example-rnv0-lG9yKU.zh-CN.vtt 1.52 KB
Part 18-Module 02-Lesson 01_Gathering Data/08. Source Scraping Webpages-ZqTad6Usf9g.zh-CN.vtt 1.52 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.pt-BR.vtt 1.52 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/13. Mu-GXY-iMfZTn0.zh-CN.vtt 1.52 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.pt-BR.vtt 1.52 KB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.en-US.vtt 1.52 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.en.vtt 1.52 KB
Part 18-Module 04-Lesson 01_Cleaning Data/20. Conclusion -d_nKtLo5WYA.zh-CN.vtt 1.52 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.es-MX.vtt 1.52 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.en.vtt 1.52 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.en.vtt 1.52 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular-FQoVv3o8vQg.en.vtt 1.51 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/04. What's Normalized-T_LpzJl-EVE.en.vtt 1.51 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.ar.vtt 1.51 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.en.vtt 1.51 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.pt-BR.vtt 1.51 KB
Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.pt-BR.vtt 1.51 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.ar.vtt 1.51 KB
Part 15-Module 01-Lesson 02_Design Principles/01. Introduction-Q0lZkNF6O0g.en.vtt 1.51 KB
Part 19-Module 01-Lesson 02_Design/01. Introduction-Q0lZkNF6O0g.en.vtt 1.51 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.pt-BR.vtt 1.51 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.en.vtt 1.51 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.ar.vtt 1.51 KB
Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.pt-BR.vtt 1.51 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.en.vtt 1.51 KB
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-Hb2q-o4ElV4.zh-CN.vtt 1.51 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/07. ggpairs Function-XUZIGbX3JIg.zh-CN.vtt 1.51 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.pt-BR.vtt 1.51 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.ar.vtt 1.51 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-HTuI3iFzOdU.zh-CN.vtt 1.51 KB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.en.vtt 1.51 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.pt-BR.vtt 1.51 KB
Part 16-Module 03-Lesson 01_Basic SQL/46. OR Statement-DRmkKVhe6-s.zh-CN.vtt 1.51 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.es.vtt 1.51 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.es.vtt 1.51 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.pt-BR.vtt 1.51 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.pt-BR.vtt 1.51 KB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.pt-BR.vtt 1.51 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.en.vtt 1.51 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.ar.vtt 1.51 KB
Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.pt-BR.vtt 1.51 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.pt-BR.vtt 1.51 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/22. in Operator-8iX-7hwKX1Q.zh-CN.vtt 1.51 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.es.vtt 1.51 KB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.pt-BR.vtt 1.51 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.pt-BR.vtt 1.51 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.en.vtt 1.51 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.pt-BR.vtt 1.5 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.pt-BR.vtt 1.5 KB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.pt-BR.vtt 1.5 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.pt-BR.vtt 1.5 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.pt-BR.vtt 1.5 KB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.en.vtt 1.5 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 1-APRpwqFpGwI.zh-CN.vtt 1.5 KB
Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.en.vtt 1.5 KB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.en.vtt 1.5 KB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.ar.vtt 1.5 KB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.en.vtt 1.5 KB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-X_AS8NBngsk.zh-CN.vtt 1.5 KB
Part 17-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.pt-BR.vtt 1.5 KB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_afLozDIcLw.en.vtt 1.5 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/16. Pandas Series apply()-lhcl1UjM_0Q.pt-BR.vtt 1.5 KB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.en.vtt 1.5 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.ar.vtt 1.5 KB
Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.pt-BR.vtt 1.5 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.pt-BR.vtt 1.5 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-3kH4ei9l4h8.zh-CN.vtt 1.5 KB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en-US.vtt 1.5 KB
Part 11-Module 01-Lesson 03_SVM/12. Coding Up the SVM-2ieszOqnpWs.zh-CN.vtt 1.5 KB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.ar.vtt 1.5 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.en.vtt 1.5 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.hr.vtt 1.5 KB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.en.vtt 1.5 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.en.vtt 1.5 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/27. Communication-P36LwI-R2Vw.zh-CN.vtt 1.5 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-mZgPfxFOFRE.ja.vtt 1.5 KB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.ar.vtt 1.5 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/04. Iterative Process-m2qDeWrGIDI.zh-CN.vtt 1.5 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.pt-BR.vtt 1.5 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Intro -FnUrE4dhgh8.zh-CN.vtt 1.5 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.ja.vtt 1.5 KB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.pt-BR.vtt 1.5 KB
Part 13-Module 01-Lesson 05_Dimple.js/27. Bar Chart The Bad-FCapLzYUQSo.zh-CN.vtt 1.5 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/06. Subqueries Part II-jko-RrZd0R8.zh-CN.vtt 1.5 KB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.pt-BR.vtt 1.5 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.pt-BR.vtt 1.5 KB
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-E63RZli2F2o.pt-BR.vtt 1.5 KB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.en.vtt 1.5 KB
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.ar.vtt 1.5 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-FGtU7YDLX2Y.en.vtt 1.49 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.en.vtt 1.49 KB
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.ar.vtt 1.49 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.pt-BR.vtt 1.49 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-0O_5vNJycJg.en.vtt 1.49 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.en.vtt 1.49 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.pt-BR.vtt 1.49 KB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.ja.vtt 1.49 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-VkQwfVQ00EQ.zh-CN.vtt 1.49 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.en.vtt 1.49 KB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.en.vtt 1.49 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.pt-BR.vtt 1.49 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-kWsDkFkEjNM.en.vtt 1.49 KB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.pt-BR.vtt 1.49 KB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.pt-BR.vtt 1.49 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-q46nO0mznXM.zh-CN.vtt 1.49 KB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.ar.vtt 1.49 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.en.vtt 1.49 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/19. Clean Programmatic Data Cleaning Process-9-T1CFuOqdQ.zh-CN.vtt 1.49 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.es-ES.vtt 1.49 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.es-ES.vtt 1.49 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.pt-BR.vtt 1.49 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.en-US.vtt 1.49 KB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.en.vtt 1.49 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.pt-BR.vtt 1.49 KB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.en.vtt 1.49 KB
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Part 14-Module 01-Lesson 04_Designing an Experiment/05. Consistency of Diversion Example-nsG26Dz9z44.zh-CN.vtt 1.49 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.en.vtt 1.49 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/21. Best Practices for Scraping-97FYi0SQFQ8.en.vtt 1.49 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-7lKhG9bIMhs.en.vtt 1.49 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.zh-CN.vtt 1.49 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-oTZO4DxRbAU.zh-CN.vtt 1.49 KB
Part 03-Module 01-Lesson 20_L8 Estimation/27. Results from Sample-ypIyvJyZAs8.zh-CN.vtt 1.49 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.en.vtt 1.49 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.es.vtt 1.49 KB
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-mIBKd-JBnXY.zh-CN.vtt 1.49 KB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.pt-BR.vtt 1.49 KB
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-L_JV4fbRAfA.zh-CN.vtt 1.49 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.en.vtt 1.49 KB
Part 11-Module 01-Lesson 01_Welcome to Machine Learning/03. Introduction Pt. III-0ZuxGhiqo5U.en.vtt 1.49 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.en.vtt 1.49 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.ar.vtt 1.49 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.en.vtt 1.48 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.ar.vtt 1.48 KB
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.pt-BR.vtt 1.48 KB
Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.pt-BR.vtt 1.48 KB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.ja.vtt 1.48 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.en.vtt 1.48 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.en.vtt 1.48 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.ar.vtt 1.48 KB
Part 11-Module 01-Lesson 08_Outliers/08. Outliers Mini-Project Video-GRN0Whyy4Lk.en.vtt 1.48 KB
Part 12-Module 01-Lesson 01_Ace Your Interview/01. Introduction-pg4HUMgKLxI.es-MX.vtt 1.48 KB
Part 13-Module 01-Lesson 07_Narrative Structures/20. The Martini Glass-h8b8SOsSiT4.zh-CN.vtt 1.48 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.ar.vtt 1.48 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.en-US.vtt 1.48 KB
Part 09-Module 01-Lesson 03_Explore One Variable/16. Statistics 'by' Gender-GTLvqNrAETc.zh-CN.vtt 1.48 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.pt-BR.vtt 1.48 KB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.en.vtt 1.48 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.en.vtt 1.48 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.pt-BR.vtt 1.48 KB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-qHk-FRWnYAo.zh-CN.vtt 1.48 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.en.vtt 1.48 KB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.en.vtt 1.48 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.ar.vtt 1.48 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/30. Filtering-vXGDYzAo22Y.zh-CN.vtt 1.48 KB
Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.en.vtt 1.48 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-iu6CxSkq-wg.zh-CN.vtt 1.48 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.en.vtt 1.48 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Tableau Desktop Download-End96VkLQc4.en.vtt 1.48 KB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.pt-BR.vtt 1.48 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.pt-BR.vtt 1.48 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-6kdmc3iTf78.zh-CN.vtt 1.47 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-qzs-3ltgTGo.zh-CN.vtt 1.47 KB
Part 11-Module 01-Lesson 11_Text Learning/07. Low-Information Words-8ZvLpWDITn4.zh-CN.vtt 1.47 KB
Part 13-Module 01-Lesson 05_Dimple.js/13. Adding an Axis with Dimple-7okDT6V9Mmk.zh-CN.vtt 1.47 KB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.ar.vtt 1.47 KB
Part 13-Module 01-Lesson 07_Narrative Structures/44. Parsing Overview and Parsing Attendance-_tVC3JuW7to.zh-CN.vtt 1.47 KB
Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.en.vtt 1.47 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/13. One-Sample t-Test-IdP9Ps2tHgw.zh-CN.vtt 1.47 KB
Part 17-Module 01-Lesson 14_Regression/08. Correlation Coefficients-rL5Bn8Fi-zE.zh-CN.vtt 1.47 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/11. Correlation Coefficients-rL5Bn8Fi-zE.zh-CN.vtt 1.47 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/07. Loading Data into a DataFrame-N66_j0gxuhg.en.vtt 1.47 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/12. Plot Colors for Qualitative Factors-2ZVGl6LrOPw.en.vtt 1.47 KB
Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.pt-BR.vtt 1.47 KB
Part 18-Module 03-Lesson 01_Assessing Data/18. Tidiness Programmatic Assessment -YrX-oiFilyA.zh-CN.vtt 1.47 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/07. Loading Data into a DataFrame-N66_j0gxuhg.en.vtt 1.47 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.ar.vtt 1.47 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.pt-BR.vtt 1.47 KB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.en-US.vtt 1.47 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.ar.vtt 1.47 KB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.pt-BR.vtt 1.47 KB
Part 13-Module 01-Lesson 05_Dimple.js/19. Adding the Series and Drawing the Chart-2zcZXJzW0aw.en.vtt 1.47 KB
Part 16-Module 03-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.en.vtt 1.47 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.en.vtt 1.47 KB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.en.vtt 1.47 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.ar.vtt 1.47 KB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.ar.vtt 1.47 KB
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance-QReeBef_7vM.zh-CN.vtt 1.47 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/03. Types of Effect-Size Measures-FWSS2VadyBg.zh-CN.vtt 1.47 KB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-e8zSXnyskro.pt-BR.vtt 1.47 KB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.ar.vtt 1.47 KB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.en.vtt 1.46 KB
Part 13-Module 01-Lesson 07_Narrative Structures/60. Context for the Reader-_GkNEO9qeWI.zh-CN.vtt 1.46 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.pt-BR.vtt 1.46 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/17. Performance Tuning 3-hIAE8W6x5O8.zh-CN.vtt 1.46 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.ar.vtt 1.46 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.pt-BR.vtt 1.46 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.en.vtt 1.46 KB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.en.vtt 1.46 KB
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/03. Cover Letter Components-DVvLiKedRw4.zh-CN.vtt 1.46 KB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.ja.vtt 1.46 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.ar.vtt 1.46 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.pt-BR.vtt 1.46 KB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.pt-BR.vtt 1.46 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.pt-BR.vtt 1.46 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.pt-BR.vtt 1.46 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.ja.vtt 1.46 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.ar.vtt 1.46 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-bjk5m0wrj3w.zh-CN.vtt 1.46 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/03. Shortcomings of Accuracy-UMWsyRYnfPk.zh-CN.vtt 1.46 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.pt-BR.vtt 1.46 KB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.pt-BR.vtt 1.46 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-TSw2AAaKxBA.zh-CN.vtt 1.46 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/08. Extracting Data-OeiBJ_D-ZsM.zh-CN.vtt 1.46 KB
Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.en.vtt 1.46 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.en.vtt 1.46 KB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.ar.vtt 1.46 KB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-CxAxRCv9WoA.zh-CN.vtt 1.46 KB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.ar.vtt 1.46 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.pt-BR.vtt 1.46 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.ar.vtt 1.46 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/11. Reading Excel Files-_Lp_3KUltFk.zh-CN.vtt 1.46 KB
Part 13-Module 01-Lesson 04_Design Principles/45. The Grammar of Graphics-AdRbdZhLn04.zh-CN.vtt 1.46 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.ar.vtt 1.45 KB
Part 13-Module 01-Lesson 07_Narrative Structures/51. Where are the Circles-hUmXWHOPxpI.zh-CN.vtt 1.45 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-ytUY1_EfxPk.pt-BR.vtt 1.45 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/08. t-Table-lccjSiVTx7c.zh-CN.vtt 1.45 KB
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-1txkcmxk3vU.zh-CN.vtt 1.45 KB
Part 03-Module 01-Lesson 20_L8 Estimation/23. CI Bounds-T9VX2KvzJ-k.zh-CN.vtt 1.45 KB
Part 05-Module 02-Lesson 01_Data and Tables/07. Anatomy of a Table-PhvA7DCgtpw.pt-BR.vtt 1.45 KB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.en.vtt 1.45 KB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.pt-BR.vtt 1.45 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.pt-BR.vtt 1.45 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.ja.vtt 1.45 KB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.pt-BR.vtt 1.45 KB
Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.ar.vtt 1.45 KB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.ar.vtt 1.45 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/21. Querying Arrays Using Scalars-8uhfnWgiBHM.zh-CN.vtt 1.45 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.pt-BR.vtt 1.45 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.ar.vtt 1.45 KB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.en.vtt 1.45 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.pt-BR.vtt 1.45 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.en.vtt 1.45 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/18. Histograms Revisited-QII0tSAIex0.ja.vtt 1.45 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.ar.vtt 1.45 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.ar.vtt 1.45 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.pt-BR.vtt 1.45 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/03. Fitting A Multiple Linear Regression Model-EZNvBF66_b0.zh-CN.vtt 1.45 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.en.vtt 1.45 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.ar.vtt 1.45 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.en.vtt 1.45 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.pt-BR.vtt 1.45 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/24. There Must Be A Better Way-oBp8YX2AgJw.zh-CN.vtt 1.45 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.es-ES.vtt 1.45 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.zh-CN.vtt 1.45 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/20. Visualize Relationship-fffGVf6-1-Y.zh-CN.vtt 1.45 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/06. r^2-X5F1reyQ_5U.en.vtt 1.45 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.ar.vtt 1.45 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.ar.vtt 1.45 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.ar.vtt 1.45 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/02. Scatterplots and Perceived Audience Size-0XndEtOLwhk.zh-CN.vtt 1.45 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.ja.vtt 1.45 KB
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-iCTPBcowJRY.pt-BR.vtt 1.45 KB
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-Oyo2HOJstCs.zh-CN.vtt 1.44 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/23. Age with Months Means-CuMPjPESfY0.ja.vtt 1.44 KB
Part 12-Module 01-Lesson 02_Practice Behavioral Questions/05. What Motivates You at the Workplace-Aa9SFwiRbho.en.vtt 1.44 KB
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-UjyPKvNHz4A.zh-CN.vtt 1.44 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.zh-CN.vtt 1.44 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.es-ES.vtt 1.44 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.pt-BR.vtt 1.44 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.ar.vtt 1.44 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.en.vtt 1.44 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.en.vtt 1.44 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.pt-BR.vtt 1.44 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/23. The Limits of Cross Sectional Data-D7m25cvqUpw.en.vtt 1.44 KB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.ar.vtt 1.44 KB
Part 05-Module 02-Lesson 03_Elements of SQL/07. The One Thing SQL is Terrible At-wrjCB1abNyM.zh-CN.vtt 1.44 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.en.vtt 1.44 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.en.vtt 1.44 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.pt-BR.vtt 1.44 KB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.ar.vtt 1.44 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.en.vtt 1.44 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.zh-CN.vtt 1.44 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/25. Causal Inference-Ozsae1O5LYs.zh-CN.vtt 1.44 KB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.ar.vtt 1.44 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.pt-BR.vtt 1.44 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.pt-BR.vtt 1.44 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/04. NumPy Axis-k8Ru6RQJbd4.zh-CN.vtt 1.44 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/04. Picking the Most Suitable Metric-GAfPvj2SSiE.zh-CN.vtt 1.44 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/04. NumPy Axis-k8Ru6RQJbd4.zh-CN.vtt 1.44 KB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.pt-BR.vtt 1.44 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.ar.vtt 1.44 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.pt-BR.vtt 1.43 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-gBdKhmtrtG8.zh-CN.vtt 1.43 KB
Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.ar.vtt 1.43 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.pt-BR.vtt 1.43 KB
Part 19-Module 01-Lesson 02_Design/02. Lesson Overview-Gg77PqkQkhs.zh-CN.vtt 1.43 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.ja.vtt 1.43 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-MEtIAGKweXU.zh-CN.vtt 1.43 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.pt-BR.vtt 1.43 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-KrZpJwPlSbA.zh-CN.vtt 1.43 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.es-MX.vtt 1.43 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.en.vtt 1.43 KB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.pt-BR.vtt 1.43 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.pt-BR.vtt 1.43 KB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.ar.vtt 1.43 KB
Part 05-Module 01-Lesson 05_Data Quality/02. What is Data Cleaning-dzqOwmxK3j4.pt-BR.vtt 1.43 KB
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-nNR4hjhhGBc.zh-CN.vtt 1.43 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.en.vtt 1.43 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.en.vtt 1.43 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.zh-CN.vtt 1.43 KB
Part 18-Module 02-Lesson 01_Gathering Data/21. Storing Data-hcosH34b-yw.en.vtt 1.43 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.en.vtt 1.43 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.en.vtt 1.43 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/25. Reassess and Iterate-eu1gO_76pSY.zh-CN.vtt 1.43 KB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.ko.vtt 1.43 KB
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Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.en.vtt 1.43 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/08. Hash Maps-A-ahUVi8pYQ.zh-CN.vtt 1.43 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.pt-BR.vtt 1.43 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/28. Conclusion-rrSNkPGJmTc.zh-CN.vtt 1.43 KB
Part 14-Module 01-Lesson 05_Analyzing Results/04. Choosing Invariants, Part 2-XqEQG4qo94I.en.vtt 1.43 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.en.vtt 1.43 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/19. What is Notation-MaHV5cKfcmE.zh-CN.vtt 1.43 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.en.vtt 1.43 KB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.ja.vtt 1.43 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/18. Recreating China's Red Dot-tDRHSTivs4k.zh-CN.vtt 1.43 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.pt-BR.vtt 1.42 KB
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.ar.vtt 1.42 KB
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Part 17-Module 01-Lesson 16_Logistic Regression/01. Introduction to Logistic Regression-P_f2RjjnPEg.zh-CN.vtt 1.42 KB
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Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.en.vtt 1.42 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/10. Gather Unzip Solution -Pzy8nHA_EJc.pt-BR.vtt 1.42 KB
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Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.ar.vtt 1.42 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.en.vtt 1.42 KB
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.ar.vtt 1.42 KB
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Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.pt-BR.vtt 1.42 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.pt-BR.vtt 1.42 KB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.en.vtt 1.42 KB
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Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.en.vtt 1.42 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/11. Data Vis in Data Science-e_-61K3jK1Y.zh-CN.vtt 1.42 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-tEmdl6zhvgA.zh-CN.vtt 1.42 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.en.vtt 1.42 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.pt-BR.vtt 1.42 KB
Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.ar.vtt 1.42 KB
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Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.ar.vtt 1.42 KB
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Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.pt-BR.vtt 1.41 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bgyN3RO2ICo.zh-CN.vtt 1.41 KB
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bgyN3RO2ICo.zh-CN.vtt 1.41 KB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.ja.vtt 1.41 KB
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Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.ar.vtt 1.41 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.pt-BR.vtt 1.41 KB
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Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.en.vtt 1.41 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.pt-BR.vtt 1.41 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.ar.vtt 1.41 KB
Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.pt-BR.vtt 1.41 KB
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Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.en.vtt 1.41 KB
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Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.en.vtt 1.41 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-rQivl4aJCOI.pt-BR.vtt 1.41 KB
Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.pt-BR.vtt 1.41 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/01. Introduction-aAmMK8tGEYc.zh-CN.vtt 1.41 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.pt-BR.vtt 1.41 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-rQivl4aJCOI.pt-BR.vtt 1.41 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/29. Decision Errors-TJ_p0xBI9bI.zh-CN.vtt 1.41 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.pt-BR.vtt 1.41 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.en.vtt 1.4 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.pt-BR.vtt 1.4 KB
Part 03-Module 01-Lesson 20_L8 Estimation/05. Approximate Margin of Error-P4gLGxQrKjY.zh-CN.vtt 1.4 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-cRb2ONJAvog.pt-BR.vtt 1.4 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-y27MBpbnP48.en.vtt 1.4 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.ja.vtt 1.4 KB
Part 10-Module 01-Lesson 01_Develop Your Personal Brand/06. Pitching to a Recruiter-LxAdWaA-qTQ.pt-BR.vtt 1.4 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.en.vtt 1.4 KB
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.ar.vtt 1.4 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/18. Critical Values of Z-_vKCQnll45c.zh-CN.vtt 1.4 KB
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Part 09-Module 01-Lesson 07_Explore Many Variables/09. Third Quantitative Variable-sS-lw3LxATY.en.vtt 1.4 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.en.vtt 1.4 KB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.en.vtt 1.4 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.ar.vtt 1.4 KB
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Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.en.vtt 1.4 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.ar.vtt 1.4 KB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.it.vtt 1.4 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-GUD6yl0A1Aw.zh-CN.vtt 1.4 KB
Part 09-Module 01-Lesson 03_Explore One Variable/05. Moira's Investigation-Mak839YmmrA.zh-CN.vtt 1.4 KB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.en.vtt 1.39 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-KuihzV_LLAE.zh-CN.vtt 1.39 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.ar.vtt 1.39 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-LuI1poHmFOw.pt-BR.vtt 1.39 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.en.vtt 1.39 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.zh-CN.vtt 1.39 KB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.en.vtt 1.39 KB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.ar.vtt 1.39 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.en.vtt 1.39 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ja.vtt 1.39 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.en.vtt 1.39 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.ar.vtt 1.39 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.pt-BR.vtt 1.39 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/13. Dummy Variables Recap-r7Lek8rsIcg.zh-CN.vtt 1.39 KB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.pt-BR.vtt 1.39 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.en.vtt 1.39 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.en.vtt 1.39 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.en.vtt 1.39 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.ar.vtt 1.39 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-kFKsCAyiPuY.zh-CN.vtt 1.39 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-kFKsCAyiPuY.zh-CN.vtt 1.39 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.en.vtt 1.39 KB
Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.ar.vtt 1.39 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.en.vtt 1.39 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-oJXYNArEk8k.zh-CN.vtt 1.39 KB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.ja.vtt 1.39 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.en.vtt 1.39 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/04. Further Motivation-sjGxUKrbKoI.zh-CN.vtt 1.39 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.ar.vtt 1.39 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.ja.vtt 1.39 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.ar.vtt 1.39 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.ar.vtt 1.39 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-n0lluEhKUfQ.zh-CN.vtt 1.39 KB
Part 11-Module 01-Lesson 02_Naive Bayes/38. Naive Bayes Mini-Project Video-UH2oSijkszo.zh-CN.vtt 1.39 KB
Part 13-Module 01-Lesson 07_Narrative Structures/58. Juxtaposition and Comparison-abaD-wvlbkg.zh-CN.vtt 1.39 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.en.vtt 1.38 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.en.vtt 1.38 KB
Part 17-Module 01-Lesson 14_Regression/17. How Do We Know If Our Model Fits Well-0vPtPAqMHJE.zh-CN.vtt 1.38 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.en.vtt 1.38 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.pt-BR.vtt 1.38 KB
Part 11-Module 01-Lesson 14_Validation/15. Validation Mini-Project Video-dlbeMlRoFd4.zh-CN.vtt 1.38 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.en.vtt 1.38 KB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.en.vtt 1.38 KB
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Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/02. Histograms-4t10RgUv2Fc.zh-CN.vtt 1.38 KB
Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.en.vtt 1.38 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.en.vtt 1.38 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.en.vtt 1.38 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-wV-6gQepmn0.zh-CN.vtt 1.38 KB
Part 09-Module 01-Lesson 02_R Basics/16. Advice for Data Scientists-FdkhUOtHIFg.ja.vtt 1.38 KB
Part 11-Module 01-Lesson 04_Decision Trees/32. Tuning Criterion Parameter-V80QLNK5fFQ.zh-CN.vtt 1.38 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.pt-BR.vtt 1.38 KB
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Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/09. NumPy Index Arrays-93y6ms_fuQQ.zh-CN.vtt 1.38 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/35. Using Sensor Data-vhl-SADfti8.zh-CN.vtt 1.38 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/10. NumPy Index Arrays-93y6ms_fuQQ.zh-CN.vtt 1.38 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.it.vtt 1.38 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.en.vtt 1.38 KB
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.pt-BR.vtt 1.38 KB
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Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.en.vtt 1.38 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.en.vtt 1.38 KB
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Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.es.vtt 1.38 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.es.vtt 1.38 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.pt-BR.vtt 1.38 KB
Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.ja.vtt 1.38 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/50. Goodbye and Keep Learning-B4EKdtRmv60.zh-CN.vtt 1.38 KB
Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.pt-BR.vtt 1.38 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.pt-BR.vtt 1.38 KB
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-GsSoLVhZPnA.zh-CN.vtt 1.38 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.pt-BR.vtt 1.38 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.en.vtt 1.38 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.pt-BR.vtt 1.38 KB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.en.vtt 1.38 KB
Part 11-Module 01-Lesson 03_SVM/16. Visualizing the New Feature-sAdM20gFi2M.zh-CN.vtt 1.38 KB
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.ja.vtt 1.38 KB
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-HyjBus7S2gY.zh-CN.vtt 1.37 KB
Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.ar.vtt 1.37 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.pt-BR.vtt 1.37 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.pt-BR.vtt 1.34 KB
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Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.pt-BR.vtt 1.32 KB
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Part 11-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.pt-BR.vtt 1.32 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/28. D3 Unpacking The Name-xPZOSx1q_dg.zh-CN.vtt 1.32 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/17. Pandas Series apply()-lhcl1UjM_0Q.zh-CN.vtt 1.32 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.ar.vtt 1.32 KB
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.ar.vtt 1.32 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.ja.vtt 1.32 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.ar.vtt 1.32 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.pt-BR.vtt 1.32 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.pt-BR.vtt 1.32 KB
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.ar.vtt 1.32 KB
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Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-UXLEe6bNpM4.zh-CN.vtt 1.32 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.ar.vtt 1.32 KB
Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.ar.vtt 1.32 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.en.vtt 1.32 KB
Part 11-Module 01-Lesson 12_Feature Selection/01. Why Feature Selection-S-xe0-XNo4I.zh-CN.vtt 1.32 KB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.es-ES.vtt 1.32 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.pt-BR.vtt 1.32 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.pt-BR.vtt 1.32 KB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.pt-BR.vtt 1.32 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.en.vtt 1.32 KB
Part 11-Module 01-Lesson 12_Feature Selection/08. Features != Information-GOrv8faKHV4.zh-CN.vtt 1.32 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.ar.vtt 1.32 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.ar.vtt 1.32 KB
Part 16-Module 03-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.zh-CN.vtt 1.32 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. Types Of Statements-vLvJbIz94C4.zh-CN.vtt 1.32 KB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.pt-BR.vtt 1.32 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score-iHnjTqGPbVg.zh-CN.vtt 1.32 KB
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.ar.vtt 1.32 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.en.vtt 1.32 KB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.pt-BR.vtt 1.32 KB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.ar.vtt 1.32 KB
Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.pt-BR.vtt 1.32 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.pt-BR.vtt 1.31 KB
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-EOLzooGccPc.zh-CN.vtt 1.31 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.en-US.vtt 1.31 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.es.vtt 1.31 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.pt-BR.vtt 1.31 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.pt-BR.vtt 1.31 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.en.vtt 1.31 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.en.vtt 1.31 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.ar.vtt 1.31 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.ar.vtt 1.31 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.pt-BR.vtt 1.31 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.pt-BR.vtt 1.31 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations-q5PjL9GkVtM.zh-CN.vtt 1.31 KB
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.ar.vtt 1.31 KB
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Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.ar.vtt 1.31 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.en.vtt 1.31 KB
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/32. Random Assignment-5AjiR_nLH2M.zh-CN.vtt 1.31 KB
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Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-xUkquw-73BY.zh-CN.vtt 1.31 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.pt-BR.vtt 1.31 KB
Part 09-Module 01-Lesson 03_Explore One Variable/17. Tenure-095MTpItufM.zh-CN.vtt 1.31 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/13. Explanatory vs Exploratory-SHq_zbB4ITo.zh-CN.vtt 1.31 KB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.pt-BR.vtt 1.31 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/13. Karma-cNFMJpVQlKY.en.vtt 1.31 KB
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Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.ja.vtt 1.31 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.zh-CN.vtt 1.31 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.pt-BR.vtt 1.31 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.en.vtt 1.31 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.ja.vtt 1.31 KB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-MXXTeWLXliY.zh-CN.vtt 1.31 KB
Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.en.vtt 1.31 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.en.vtt 1.31 KB
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.pt-BR.vtt 1.31 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.en.vtt 1.31 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.es.vtt 1.31 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.es.vtt 1.31 KB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.en.vtt 1.31 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-P1aYwQhPnPQ.zh-CN.vtt 1.31 KB
Part 17-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.en.vtt 1.31 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.zh-Hans.vtt 1.31 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.en.vtt 1.31 KB
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-ncFtwW5urHk.zh-CN.vtt 1.31 KB
Part 17-Module 01-Lesson 11_Confidence Intervals/07. Confidence Intervals Applications-C0wgmeRx9yE.zh-CN.vtt 1.31 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.pt-BR.vtt 1.3 KB
Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.pt-BR.vtt 1.3 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-4hoT_su75AQ.zh-CN.vtt 1.3 KB
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.hi.vtt 1.3 KB
Part 13-Module 01-Lesson 07_Narrative Structures/15. One Human Heartbeat-unKu-dmor2w.zh-CN.vtt 1.3 KB
Part 13-Module 01-Lesson 07_Narrative Structures/26. Thinking with Joins-HGQ25_ivLMQ.zh-CN.vtt 1.3 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-OT2aD9XgOWg.zh-CN.vtt 1.3 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-OT2aD9XgOWg.zh-CN.vtt 1.3 KB
Part 03-Module 01-Lesson 20_L8 Estimation/15. Bigger Sample, Smaller CI-DRarpjC23kc.zh-CN.vtt 1.3 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-mb1eR8nb9t4.pt-BR.vtt 1.3 KB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.pt-BR.vtt 1.3 KB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.en.vtt 1.3 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.pt-BR.vtt 1.3 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.pt-BR.vtt 1.3 KB
Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.en.vtt 1.3 KB
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-lCWGV6ZuXt0.zh-CN.vtt 1.3 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.ar.vtt 1.3 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.pt-BR.vtt 1.3 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-OVeEr0CSe8U.en.vtt 1.3 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-pjBOYFAkNME.zh-CN.vtt 1.3 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.en.vtt 1.3 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.en.vtt 1.3 KB
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3--XfG5hXveiE.pt-BR.vtt 1.3 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/21. Size vs. Power Trade-Off-bnTIVGBkKhM.zh-CN.vtt 1.3 KB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.pt-BR.vtt 1.3 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.pt-BR.vtt 1.3 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.pt-BR.vtt 1.3 KB
Part 07-Module 01-Lesson 01_GitHub Review/14. Participating in open source projects 2-elZCLxVvJrY.zh-CN.vtt 1.3 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.pt-BR.vtt 1.3 KB
Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.en.vtt 1.3 KB
Part 16-Module 03-Lesson 01_Basic SQL/01. Introduction-Z8WNfx9Oq9s.zh-CN.vtt 1.3 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.zh-CN.vtt 1.3 KB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.en.vtt 1.29 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -iT1vtUy2utg.zh-CN.vtt 1.29 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6-eqFgLu0eqBE.zh-CN.vtt 1.29 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.ar.vtt 1.29 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.pt-BR.vtt 1.29 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.pt-BR.vtt 1.29 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.en.vtt 1.29 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.pt-BR.vtt 1.29 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/35. Visualization and D3 Basics-ueKb1OghNEU.zh-CN.vtt 1.29 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.pt-BR.vtt 1.29 KB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.pt-BR.vtt 1.29 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.en.vtt 1.29 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.ar.vtt 1.29 KB
Part 16-Module 03-Lesson 01_Basic SQL/37. IN Operator-_JPO7wwX3uA.zh-CN.vtt 1.29 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.en.vtt 1.29 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.ar.vtt 1.29 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.en.vtt 1.29 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.en.vtt 1.29 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.zh-CN.vtt 1.29 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.zh-CN.vtt 1.29 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.ar.vtt 1.29 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.pt-BR.vtt 1.29 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.ar.vtt 1.29 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/14. Correlation Methods-VQJCYk643po.zh-CN.vtt 1.29 KB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.zh-Hans.vtt 1.29 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/22. Understanding Noise Age to Age Months-cUDZ1vkmdnk.zh-CN.vtt 1.29 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.zh-CN.vtt 1.29 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/12. Unpopular-FQoVv3o8vQg.zh-CN.vtt 1.29 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.en.vtt 1.29 KB
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.pt-BR.vtt 1.29 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.pt-BR.vtt 1.29 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.en.vtt 1.29 KB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.pt-BR.vtt 1.29 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.en.vtt 1.28 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.en.vtt 1.28 KB
Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.ja.vtt 1.28 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.es-ES.vtt 1.28 KB
Part 11-Module 01-Lesson 13_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.zh-CN.vtt 1.28 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.zh-CN.vtt 1.28 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.en.vtt 1.28 KB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.en.vtt 1.28 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.pt-BR.vtt 1.28 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/05. Cohen's d-5rXOy1S5bVk.zh-CN.vtt 1.28 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.pt-BR.vtt 1.28 KB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.en.vtt 1.28 KB
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Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.en.vtt 1.28 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-gTTwyzbOOgU.en.vtt 1.28 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.pt-BR.vtt 1.28 KB
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Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.en.vtt 1.28 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.it.vtt 1.28 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.pt-BR.vtt 1.28 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.pt-BR.vtt 1.28 KB
Part 11-Module 01-Lesson 03_SVM/13. Nonlinear SVMs-6UgInp_gf1w.zh-CN.vtt 1.28 KB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.pt-BR.vtt 1.28 KB
Part 11-Module 01-Lesson 14_Validation/01. Cross Validation for Fun and Profit-VkUpuABChT4.zh-CN.vtt 1.28 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.pt-BR.vtt 1.28 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.en.vtt 1.28 KB
Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.pt-BR.vtt 1.28 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.zh-TW.vtt 1.28 KB
Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.en.vtt 1.28 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.en.vtt 1.28 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/13. DataFrame apply() Use Case 2-C6okqt-jf08.zh-CN.vtt 1.28 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.pt-BR.vtt 1.28 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/13. DataFrame apply() Use Case 2-C6okqt-jf08.zh-CN.vtt 1.28 KB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-NRCs22HJ-vI.zh-CN.vtt 1.28 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.pt-BR.vtt 1.27 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/24. all Operator-B3iYl-2HSXI.zh-CN.vtt 1.27 KB
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Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.en.vtt 1.27 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.pt-BR.vtt 1.27 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.pt-BR.vtt 1.27 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.en.vtt 1.27 KB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.pt-BR.vtt 1.27 KB
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/02. Shortest Path Problem-huKUM97Vve8.zh-CN.vtt 1.27 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/20. Win, Lose or Draw-ZhWxuf5czTA.zh-CN.vtt 1.27 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.zh-CN.vtt 1.27 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.zh-CN.vtt 1.27 KB
Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.pt-BR.vtt 1.27 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/04. COUNT-b4FCWAEGmLg.zh-CN.vtt 1.27 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.es-ES.vtt 1.27 KB
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.ar.vtt 1.27 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.pt-BR.vtt 1.27 KB
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.ar.vtt 1.27 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.ar.vtt 1.27 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/07. Ethical Considerations Example-KhGfaSWoEn0.zh-CN.vtt 1.27 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ja.vtt 1.27 KB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.en.vtt 1.27 KB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.en.vtt 1.27 KB
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Part 17-Module 01-Lesson 04_Probability/19. Probability Conclusion-dsVKoXymYDU.zh-CN.vtt 1.27 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/18. Mean and SD-e6pJfNbQEKk.zh-CN.vtt 1.27 KB
Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.ar.vtt 1.27 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.en.vtt 1.27 KB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.pt-BR.vtt 1.27 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-b0oOWFDz9UQ.zh-CN.vtt 1.27 KB
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.ar.vtt 1.27 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.en.vtt 1.27 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.ar.vtt 1.27 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/18. Hypotheses-FDcgsIOTv94.zh-CN.vtt 1.27 KB
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Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.pt-BR.vtt 1.27 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-eZ_yCrh4740.zh-CN.vtt 1.27 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.en.vtt 1.27 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.pt-BR.vtt 1.26 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.ar.vtt 1.26 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.en.vtt 1.26 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.ar.vtt 1.26 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.ar.vtt 1.26 KB
Part 18-Module 02-Lesson 01_Gathering Data/15. Source APIs (Application Programming Interfaces)-1y_qjUMDsCw.zh-CN.vtt 1.26 KB
Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.en.vtt 1.26 KB
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Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.ar.vtt 1.26 KB
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en-GB.vtt 1.26 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.en.vtt 1.26 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.en.vtt 1.26 KB
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Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.ar.vtt 1.26 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.en-US.vtt 1.26 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.ar.vtt 1.26 KB
Part 16-Module 02-Lesson 01_The Data Analysis Process/11. Data Wrangling And EDA-EQXfxbUup0o.zh-CN.vtt 1.26 KB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.en.vtt 1.26 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.ar.vtt 1.26 KB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.ar.vtt 1.26 KB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.en.vtt 1.26 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.es.vtt 1.26 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.es.vtt 1.26 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.en.vtt 1.26 KB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-7HMAtB-342I.zh-CN.vtt 1.26 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.pt-BR.vtt 1.26 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.en.vtt 1.26 KB
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-oZY94XjiCvM.zh-CN.vtt 1.26 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.pt-BR.vtt 1.26 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.en.vtt 1.26 KB
Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.pt-BR.vtt 1.26 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-c6vE21UVksU.zh-CN.vtt 1.26 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.ar.vtt 1.26 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.pt-BR.vtt 1.26 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-DIrLvDqhjCg.zh-CN.vtt 1.26 KB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.pt-BR.vtt 1.26 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.ar.vtt 1.26 KB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-rNR4_JqCEuk.zh-CN.vtt 1.26 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.en.vtt 1.26 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.pt-BR.vtt 1.25 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.pt-BR.vtt 1.25 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/40. Notation for Difference-r1X81SXRLKI.zh-CN.vtt 1.25 KB
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.ar.vtt 1.25 KB
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.pt-BR.vtt 1.25 KB
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-w5XWkq_Y-rY.zh-CN.vtt 1.25 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/09. Renaming Columns-3Oo4gUP2_Rw.zh-CN.vtt 1.25 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.pt-BR.vtt 1.25 KB
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-jfGdUdo37Vk.zh-CN.vtt 1.25 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/15. Experiment Design and Sizing Overview-6_odiPIKZO0.zh-CN.vtt 1.25 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.en.vtt 1.25 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.it.vtt 1.25 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-0m5k7Ni1O48.en.vtt 1.25 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.pt-BR.vtt 1.25 KB
Part 13-Module 01-Lesson 04_Design Principles/09. Chart Suggestions-5V109AVr_JE.zh-CN.vtt 1.25 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.ar.vtt 1.25 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.pt-BR.vtt 1.25 KB
Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.pt-BR.vtt 1.25 KB
Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.ar.vtt 1.25 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.en.vtt 1.25 KB
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-d7J0y_PSP2I.zh-CN.vtt 1.25 KB
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.pt-BR.vtt 1.25 KB
Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.pt-BR.vtt 1.25 KB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.pt-BR.vtt 1.25 KB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.pt-BR.vtt 1.25 KB
Part 09-Module 01-Lesson 01_What is EDA/07. Our Approach for This Course-dBsf-szQ00s.zh-CN.vtt 1.25 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.ar.vtt 1.25 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.en.vtt 1.25 KB
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.ar.vtt 1.25 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.en.vtt 1.25 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.en.vtt 1.25 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/12. Correlation-L9-lBQbknp0.zh-CN.vtt 1.25 KB
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-VBs6D4ggnYY.zh-CN.vtt 1.25 KB
Part 12-Module 02-Lesson 05_Trees/13. BST Complications-pcB0wV7myy4.pt-BR.vtt 1.25 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.pt-BR.vtt 1.25 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/02. Gapminder Data-lbNk216NW48.zh-CN.vtt 1.25 KB
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.ar.vtt 1.25 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.en.vtt 1.25 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/03. Gapminder Data-lbNk216NW48.zh-CN.vtt 1.25 KB
Part 03-Module 01-Lesson 11_L4 Variability/33. SD in Words-zxnijlBCSpE.zh-CN.vtt 1.25 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.en.vtt 1.25 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.pt-BR.vtt 1.25 KB
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.ar.vtt 1.25 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/02. Why Do We Use Data Visualizations-iiOP4PE46f4.zh-CN.vtt 1.25 KB
Part 11-Module 01-Lesson 08_Outliers/07. Summary of Outlier Removal Strategy-b-oE175NJiQ.zh-CN.vtt 1.24 KB
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.en.vtt 1.24 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/23. Clean Test 2-CyeB16-eGSg.zh-CN.vtt 1.24 KB
Part 21-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.zh-CN.vtt 1.24 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/09. Foreign Keys-mFPq74OMkKk.zh-CN.vtt 1.24 KB
Part 09-Module 01-Lesson 03_Explore One Variable/02. What to Do First-TgAIx_NFaD8.ja.vtt 1.24 KB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.pt-BR.vtt 1.24 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.en.vtt 1.24 KB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.en.vtt 1.24 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.en.vtt 1.24 KB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.pt-BR.vtt 1.24 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.zh-CN.vtt 1.24 KB
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.ar.vtt 1.24 KB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.en.vtt 1.24 KB
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.ar.vtt 1.24 KB
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Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-cpDTPUNDo4U.zh-CN.vtt 1.24 KB
Part 05-Module 02-Lesson 03_Elements of SQL/05. SELECT WHERE-aznzJPXavDg.zh-CN.vtt 1.24 KB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.ar.vtt 1.24 KB
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Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.en.vtt 1.24 KB
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Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.pt-BR.vtt 1.24 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Common Table Expressions-qtEKO7B8bXQ.zh-CN.vtt 1.24 KB
Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.pt-BR.vtt 1.24 KB
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-ZULplTNbIIs.zh-CN.vtt 1.24 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.pt-BR.vtt 1.24 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.en.vtt 1.24 KB
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Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.pt-BR.vtt 1.24 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.en.vtt 1.24 KB
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.pt-BR.vtt 1.24 KB
Part 03-Module 01-Lesson 20_L8 Estimation/25. Margin of Error-slBW5Neh2cs.zh-CN.vtt 1.24 KB
Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.pt-BR.vtt 1.24 KB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.en.vtt 1.24 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.pt-BR.vtt 1.24 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.pt-BR.vtt 1.24 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/26. Even More Variables-P7BHYXxu4Jg.zh-CN.vtt 1.24 KB
Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.pt-BR.vtt 1.24 KB
Part 03-Module 01-Lesson 20_L8 Estimation/26. Rate Engagement and Learning-BRL0ZuvBm0U.zh-CN.vtt 1.23 KB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.en.vtt 1.23 KB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.ar.vtt 1.23 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.pt-BR.vtt 1.23 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/25. Background Of Bootstrapping-6Vg5kGoDl7k.zh-CN.vtt 1.23 KB
Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.en.vtt 1.23 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.pt-BR.vtt 1.23 KB
Part 17-Module 01-Lesson 07_Bayes Rule/32. Reducing Uncertainty-zuFMhmKQ--o.zh-CN.vtt 1.23 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.en.vtt 1.23 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution-GNAZ2S3igr4.pt-BR.vtt 1.23 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.en.vtt 1.23 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.en.vtt 1.23 KB
Part 09-Module 01-Lesson 01_What is EDA/01. Data is Ubiquitous-ieiQqLicBjg.zh-CN.vtt 1.23 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/06. Wide and Long Format-zlaeISxRESQ.zh-CN.vtt 1.23 KB
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Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.ar.vtt 1.23 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.pt-BR.vtt 1.23 KB
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Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.pt-BR.vtt 1.23 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.ar.vtt 1.23 KB
Part 13-Module 01-Lesson 04_Design Principles/52. The Purpose of the Grammar of Graphics-pZyrfzuB5FE.zh-CN.vtt 1.23 KB
Part 14-Module 01-Lesson 04_Designing an Experiment/22. When to Limit Exposure-z_Gp9ttyiwg.zh-CN.vtt 1.23 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/06. Example of Sampling Distributions - Part I-1XezzP6kxUE.zh-CN.vtt 1.23 KB
Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.ar.vtt 1.23 KB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-pX849ta6kaI.zh-CN.vtt 1.23 KB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.es-ES.vtt 1.23 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.en.vtt 1.23 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.pt-BR.vtt 1.23 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.en.vtt 1.23 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.en.vtt 1.23 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.pt-BR.vtt 1.23 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-Fkm7ogOussQ.zh-CN.vtt 1.23 KB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.pt-BR.vtt 1.22 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.ar.vtt 1.22 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.pt-PT.vtt 1.22 KB
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.pt-BR.vtt 1.22 KB
Part 11-Module 01-Lesson 12_Feature Selection/03. A New Enron Feature Quiz-Nmf80xB1DN0.zh-CN.vtt 1.22 KB
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Ilu1JjjAbwA.zh-CN.vtt 1.22 KB
Part 11-Module 01-Lesson 14_Validation/11. Cross Validation for Parameter Tuning-Xcb9jjjAm60.zh-CN.vtt 1.22 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.es.vtt 1.22 KB
Part 13-Module 01-Lesson 04_Design Principles/50. Grammar of Graphics and D3 Functions-rADl_md-WNM.zh-CN.vtt 1.22 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.pt-BR.vtt 1.22 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.ar.vtt 1.22 KB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.en.vtt 1.22 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/27. Analysis and Visualization (Before Cleaning)-jJH3H8Rqv8s.en.vtt 1.22 KB
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-nqMT8qTmQPY.zh-CN.vtt 1.22 KB
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.ar.vtt 1.22 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/11. Z-1MZnEo0UVX4.zh-CN.vtt 1.22 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.pt-BR.vtt 1.22 KB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.ar.vtt 1.22 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-R4zq6mPPMxs.zh-CN.vtt 1.22 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.ar.vtt 1.22 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.en.vtt 1.22 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.zh-CN.vtt 1.22 KB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.ja.vtt 1.22 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.pt-BR.vtt 1.22 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.ja.vtt 1.22 KB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.ja.vtt 1.22 KB
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.th.vtt 1.22 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.pt-BR.vtt 1.22 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.pt-BR.vtt 1.22 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.pt-BR.vtt 1.22 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-4Aj_qdImmGo.zh-CN.vtt 1.22 KB
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.ar.vtt 1.22 KB
Part 11-Module 01-Lesson 07_Regressions/36. Multi-Variate Regression Quiz 2-97v0kEWjcmg.zh-CN.vtt 1.22 KB
Part 13-Module 01-Lesson 04_Design Principles/20. Negative Space-3toURbAUt9s.zh-CN.vtt 1.22 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.pt-BR.vtt 1.21 KB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.ar.vtt 1.21 KB
Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.pt-BR.vtt 1.21 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.en-US.vtt 1.21 KB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.pt-BR.vtt 1.21 KB
Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.en.vtt 1.21 KB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.ar.vtt 1.21 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.en.vtt 1.21 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.en.vtt 1.21 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Lv22Usic4A8.zh-CN.vtt 1.21 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.pt-BR.vtt 1.21 KB
Part 09-Module 01-Lesson 02_R Basics/14. Setting Levels of Ordered Factors-HSeIrqW-YGw.ja.vtt 1.21 KB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.en.vtt 1.21 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.ja.vtt 1.21 KB
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.ar.vtt 1.21 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.pt-BR.vtt 1.21 KB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.en.vtt 1.21 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.pt-BR.vtt 1.21 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.pt-BR.vtt 1.21 KB
Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.es-MX.vtt 1.21 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.en.vtt 1.21 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.ar.vtt 1.21 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.es.vtt 1.21 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1V7JzqCfe9o.zh-CN.vtt 1.21 KB
Part 11-Module 01-Lesson 07_Regressions/28. Evaluating Regression by Eye-hS7cpq-sOeQ.zh-CN.vtt 1.21 KB
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.zh-CN.vtt 1.21 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/04. More Examples-gj-or8b8TmM.zh-CN.vtt 1.21 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.ar.vtt 1.21 KB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.it.vtt 1.21 KB
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.pt-BR.vtt 1.21 KB
Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.en.vtt 1.21 KB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.pt-BR.vtt 1.21 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.en.vtt 1.21 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.pt-BR.vtt 1.21 KB
Part 06-Module 01-Lesson 01_Working with MongoDB/09. Querying Using Field Selection-V2UMNT9VBrw.zh-CN.vtt 1.21 KB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.en-US.vtt 1.21 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.pt-BR.vtt 1.21 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/10. AVG-diqCDztOL64.zh-CN.vtt 1.21 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/16. GROUP BY Part II-0HQ-TshNNQA.zh-CN.vtt 1.21 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.en.vtt 1.21 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.ar.vtt 1.21 KB
Part 11-Module 01-Lesson 02_Naive Bayes/07. Intro To Stanley Terrain Classification-TwFhCeov85E.zh-CN.vtt 1.21 KB
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.ar.vtt 1.21 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.en.vtt 1.21 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.pt-BR.vtt 1.21 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.ar.vtt 1.21 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-NI.vtt 1.2 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-Keh5GwaSWdk.zh-CN.vtt 1.2 KB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.en.vtt 1.2 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.pt-BR.vtt 1.2 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.pt-BR.vtt 1.2 KB
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-e8zSXnyskro.zh-CN.vtt 1.2 KB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.en.vtt 1.2 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.pt-BR.vtt 1.2 KB
Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.en.vtt 1.2 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/04. The Functional Art Obesity and Education-UNqgFhKvCL4.zh-CN.vtt 1.2 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/10. Integrity and Mindset-zCOr3O50gQM.zh-CN.vtt 1.2 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.es.vtt 1.2 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.es.vtt 1.2 KB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.pt-BR.vtt 1.2 KB
Part 13-Module 01-Lesson 05_Dimple.js/07. Javascript Debugger-AzbaV5CT9es.zh-CN.vtt 1.2 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.en.vtt 1.2 KB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.en.vtt 1.2 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.pt-BR.vtt 1.2 KB
Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.ar.vtt 1.2 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.es.vtt 1.2 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.pt-BR.vtt 1.2 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-p_xPoBRJdtE.zh-CN.vtt 1.2 KB
Part 18-Module 02-Lesson 01_Gathering Data/14. Text Files In Python 2-9YPOlROXNZM.zh-CN.vtt 1.2 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.pt-BR.vtt 1.2 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.ja.vtt 1.2 KB
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.pt-BR.vtt 1.2 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.pt-BR.vtt 1.2 KB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.en.vtt 1.2 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.en.vtt 1.2 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.en.vtt 1.2 KB
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-LwazT9KH76w.en.vtt 1.2 KB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.en.vtt 1.2 KB
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.zh-CN.vtt 1.2 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.ar.vtt 1.2 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.en.vtt 1.2 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.en.vtt 1.2 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.pt-BR.vtt 1.2 KB
Part 05-Module 02-Lesson 01_Data and Tables/08. Aggregations-TE9uvPwvpu4.zh-CN.vtt 1.2 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.en.vtt 1.2 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.pt-BR.vtt 1.2 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.ar.vtt 1.2 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/12. Subqueries Using WITH-IszTmDKyKHI.zh-CN.vtt 1.2 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.pt-BR.vtt 1.19 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.en.vtt 1.19 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.es.vtt 1.19 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.es.vtt 1.19 KB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.pt-BR.vtt 1.19 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-UUn6ETq08SU.zh-CN.vtt 1.19 KB
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-z-cX1kYbC1w.zh-CN.vtt 1.19 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.ja.vtt 1.19 KB
Part 13-Module 01-Lesson 07_Narrative Structures/01. Finding Stories-vVWFVaiWomw.zh-CN.vtt 1.19 KB
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.pt-BR.vtt 1.19 KB
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mPcWDYTRDs8.zh-CN.vtt 1.19 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.en.vtt 1.19 KB
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.ar.vtt 1.19 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.en.vtt 1.19 KB
Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.en.vtt 1.19 KB
Part 14-Module 01-Lesson 05_Analyzing Results/01. Introduction-AyeKXinJ3W8.zh-CN.vtt 1.19 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.en.vtt 1.19 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.en.vtt 1.19 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/28. Show Me-Jpk99mgmwaA.zh-CN.vtt 1.19 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.ar.vtt 1.19 KB
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.ar.vtt 1.19 KB
Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.en.vtt 1.19 KB
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.th.vtt 1.19 KB
Part 03-Module 01-Lesson 11_L4 Variability/32. SD Social Networkers-R6KT9-ZbQ4c.zh-CN.vtt 1.19 KB
Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.en-US.vtt 1.19 KB
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-8IzQG_2WAcs.en.vtt 1.19 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.en.vtt 1.19 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.ar.vtt 1.19 KB
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.pt-BR.vtt 1.19 KB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.en.vtt 1.19 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.en.vtt 1.19 KB
Part 11-Module 01-Lesson 03_SVM/11. SVM Decision Boundary-8hEjeR0qLnA.zh-CN.vtt 1.19 KB
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.ar.vtt 1.19 KB
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.en.vtt 1.19 KB
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.ar.vtt 1.19 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.ar.vtt 1.19 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.pt-BR.vtt 1.19 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.en.vtt 1.19 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/02. Perceived Audience Size by Age-GFKRNBnFGVU.zh-CN.vtt 1.19 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.en.vtt 1.19 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.pt-BR.vtt 1.19 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.en.vtt 1.19 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.en.vtt 1.19 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.ja.vtt 1.19 KB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.ja.vtt 1.19 KB
Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.en.vtt 1.19 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.en.vtt 1.18 KB
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Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.pt-BR.vtt 1.18 KB
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Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.pt-BR.vtt 1.18 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/06. CREATE and DROP databases-3kycKkbQK6A.zh-CN.vtt 1.18 KB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.pt-BR.vtt 1.18 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.pt-BR.vtt 1.18 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.ar.vtt 1.18 KB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.ja.vtt 1.18 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.en.vtt 1.18 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.en.vtt 1.18 KB
Part 16-Module 03-Lesson 01_Basic SQL/07. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt 1.18 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.en.vtt 1.18 KB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.en.vtt 1.18 KB
Part 18-Module 02-Lesson 01_Gathering Data/22. How Databases Store Data-H0C9z_sRvLE.zh-CN.vtt 1.18 KB
Part 07-Module 01-Lesson 01_GitHub Review/08. Writing READMEs with Walter-DQEfT2Zq5_o.zh-CN.vtt 1.18 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.ja.vtt 1.18 KB
Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.pt-BR.vtt 1.18 KB
Part 13-Module 01-Lesson 04_Design Principles/28. How Visualizations can Save Lives-VUllIatQ3tI.zh-CN.vtt 1.18 KB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.es-ES.vtt 1.18 KB
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Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.ar.vtt 1.18 KB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.pt-BR.vtt 1.18 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.pt-BR.vtt 1.18 KB
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Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.en.vtt 1.18 KB
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.ar.vtt 1.18 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/15. Why Even Create Graphics-lqI3LFwMVUc.zh-CN.vtt 1.18 KB
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/03. Why Even Create Graphics - Data Visualization and D3.js-lqI3LFwMVUc.zh-CN.vtt 1.18 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ar.vtt 1.18 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.en.vtt 1.18 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/15. Two Useful Theorems-jQ5i7CALdRQ.zh-CN.vtt 1.18 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-cRb2ONJAvog.zh-CN.vtt 1.18 KB
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Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.ar.vtt 1.18 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.en-US.vtt 1.17 KB
Part 05-Module 02-Lesson 01_Data and Tables/16. Database Concepts-PXNaLWJ5SKg.zh-CN.vtt 1.17 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.pt-BR.vtt 1.17 KB
Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.pt-BR.vtt 1.17 KB
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/21. 37. Insomnia-HbnB5SQqmoM.zh-CN.vtt 1.17 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-rQivl4aJCOI.zh-CN.vtt 1.17 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.en.vtt 1.17 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.es-ES.vtt 1.17 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.zh-CN.vtt 1.17 KB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.en.vtt 1.17 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-rQivl4aJCOI.zh-CN.vtt 1.17 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.pt-BR.vtt 1.17 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.pt-BR.vtt 1.17 KB
Part 17-Module 01-Lesson 07_Bayes Rule/29. Generalizing-SdMk3aROgSc.zh-CN.vtt 1.17 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.en.vtt 1.17 KB
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.ar.vtt 1.17 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.en.vtt 1.17 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.en.vtt 1.17 KB
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.ar.vtt 1.17 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/25. Calculating Results-SxCK2_82FfQ.zh-CN.vtt 1.17 KB
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.th.vtt 1.17 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/01. Introduction to Multiple Linear Regression-b26v8HK-8-o.zh-CN.vtt 1.17 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.en.vtt 1.17 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.es.vtt 1.17 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.en.vtt 1.17 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.ar.vtt 1.17 KB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.pt-BR.vtt 1.17 KB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.en.vtt 1.17 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.pt-BR.vtt 1.17 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.pt-BR.vtt 1.17 KB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.en.vtt 1.17 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/04. Test Cases-7CNatJ7PqZ4.pt-BR.vtt 1.17 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-19ZQP5wzmKA.zh-CN.vtt 1.17 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.it.vtt 1.17 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.en.vtt 1.17 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.en.vtt 1.17 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-ES.vtt 1.17 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.es-MX.vtt 1.17 KB
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.ar.vtt 1.17 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.es-ES.vtt 1.17 KB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.en.vtt 1.16 KB
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-2OKqKX7DnMQ.zh-CN.vtt 1.16 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.sv.vtt 1.16 KB
Part 05-Module 02-Lesson 03_Elements of SQL/11. Count All the Species-vfEi3aOawTI.zh-CN.vtt 1.16 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.ar.vtt 1.16 KB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.ja.vtt 1.16 KB
Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.pt-BR.vtt 1.16 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.en.vtt 1.16 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.en.vtt 1.16 KB
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.ar.vtt 1.16 KB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-i6nppkOcNoE.zh-CN.vtt 1.16 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.pt-BR.vtt 1.16 KB
Part 03-Module 01-Lesson 11_L4 Variability/40. Jelly Beans-1HmiArFN-EI.zh-CN.vtt 1.16 KB
Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.pt-BR.vtt 1.16 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.es-MX.vtt 1.16 KB
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.ar.vtt 1.16 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.en.vtt 1.16 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.en-US.vtt 1.16 KB
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.th.vtt 1.16 KB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.pt-BR.vtt 1.16 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-mb1eR8nb9t4.en.vtt 1.16 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.pt-BR.vtt 1.16 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.ar.vtt 1.16 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.en.vtt 1.16 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.en.vtt 1.16 KB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.pt-BR.vtt 1.16 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-QCakJ5gxF5w.zh-CN.vtt 1.16 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.pt-BR.vtt 1.16 KB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.en.vtt 1.16 KB
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.ar.vtt 1.16 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.zh-CN.vtt 1.16 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.ar.vtt 1.16 KB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.pt-BR.vtt 1.16 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/28. Udacians' Facebook Friends - Median-BHFxJmzw1gY.zh-CN.vtt 1.15 KB
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.es-MX.vtt 1.15 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.pt-BR.vtt 1.15 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.en.vtt 1.15 KB
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.pt-BR.vtt 1.15 KB
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-BngCW1fjvFk.zh-CN.vtt 1.15 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-_c_chcNiHyo.zh-CN.vtt 1.15 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.en-US.vtt 1.15 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.en.vtt 1.15 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.zh-CN.vtt 1.15 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-FLpXmoHp7eE.pt-BR.vtt 1.15 KB
Part 16-Module 03-Lesson 01_Basic SQL/02. Parch Posey Database-JOMI560DgXg.zh-CN.vtt 1.15 KB
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.th.vtt 1.15 KB
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-FLpXmoHp7eE.pt-BR.vtt 1.15 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.zh-CN.vtt 1.15 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-NymYenNcVdk.zh-CN.vtt 1.15 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.pt-BR.vtt 1.15 KB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-cwjvMYPB1Fk.zh-CN.vtt 1.15 KB
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-dkLEMSLTxvk.zh-CN.vtt 1.15 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.en.vtt 1.15 KB
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-bFDJ_FstSZ4.zh-CN.vtt 1.15 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.pt-BR.vtt 1.15 KB
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.ar.vtt 1.15 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.en.vtt 1.15 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.pt-BR.vtt 1.15 KB
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.pt-BR.vtt 1.15 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.ja.vtt 1.15 KB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.pt-BR.vtt 1.15 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-ONwh_Dcd6j8.zh-CN.vtt 1.15 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.ar.vtt 1.15 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.en-GB.vtt 1.15 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.ja.vtt 1.15 KB
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.ar.vtt 1.15 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.en.vtt 1.15 KB
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.ar.vtt 1.15 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.ar.vtt 1.15 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.en.vtt 1.15 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.es.vtt 1.15 KB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.ja.vtt 1.15 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.en.vtt 1.15 KB
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-fktfjG1SnkI.zh-CN.vtt 1.15 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.pt-BR.vtt 1.15 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots-AtmfksGs-0I.zh-CN.vtt 1.15 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.en.vtt 1.14 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.pt-BR.vtt 1.14 KB
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.ar.vtt 1.14 KB
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-bY2fuRkH3iw.zh-CN.vtt 1.14 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/26. Which Plot to Choose-pBSQI8EmhvM.zh-CN.vtt 1.14 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.pt-BR.vtt 1.14 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/19. DISTINCT-YDJEHkgKORY.zh-CN.vtt 1.14 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.ar.vtt 1.14 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.pt-PT.vtt 1.14 KB
Part 11-Module 01-Lesson 07_Regressions/37. Regression Mini-Project Video-CrD9jN3rBM8.zh-CN.vtt 1.14 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.pt-BR.vtt 1.14 KB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.en.vtt 1.14 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.en.vtt 1.14 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/04. 02 Joining Tables-vSjKBMgW1Fw.pt-BR.vtt 1.14 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.ar.vtt 1.14 KB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.en.vtt 1.14 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.tr.vtt 1.14 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.es-ES.vtt 1.14 KB
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.ar.vtt 1.14 KB
Part 17-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.zh-CN.vtt 1.14 KB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.en.vtt 1.14 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-0tcbCIrJGlM.zh-CN.vtt 1.14 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/11. Missing Engagement Records-TluBvgsphHQ.zh-CN.vtt 1.14 KB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.en.vtt 1.14 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.ca.vtt 1.14 KB
Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.en.vtt 1.14 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.ja.vtt 1.14 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.ar.vtt 1.14 KB
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.pt-BR.vtt 1.14 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.pt-BR.vtt 1.14 KB
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.en.vtt 1.14 KB
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.ar.vtt 1.14 KB
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.ar.vtt 1.14 KB
Part 11-Module 01-Lesson 04_Decision Trees/15. Formula of Entropy-NHAatuG0T3Q.zh-CN.vtt 1.14 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.en.vtt 1.14 KB
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.pt-BR.vtt 1.13 KB
Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.pt-BR.vtt 1.13 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.ja.vtt 1.13 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.en.vtt 1.13 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-oR8H9vdtreE.en.vtt 1.13 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/25. Using Sampling Distribution-NUY4Qobhojg.zh-CN.vtt 1.13 KB
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.pt-BR.vtt 1.13 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.pt-BR.vtt 1.13 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-STqN_v6Iz5o.zh-CN.vtt 1.13 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.ja.vtt 1.13 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/04. 02 Joining Tables-vSjKBMgW1Fw.en.vtt 1.13 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.ar.vtt 1.13 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.ja.vtt 1.13 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-STqN_v6Iz5o.zh-CN.vtt 1.13 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.en.vtt 1.13 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/14. Vectorized Operations and Series Indexes-QX_KFUXtHkw.zh-CN.vtt 1.13 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.ar.vtt 1.13 KB
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.ar.vtt 1.13 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/15. Vectorized Operations and Series Indexes-QX_KFUXtHkw.zh-CN.vtt 1.13 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.ja.vtt 1.13 KB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.ja.vtt 1.13 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.ja.vtt 1.13 KB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.pt-BR.vtt 1.13 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.ar.vtt 1.13 KB
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.ar.vtt 1.13 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/28. Variability Summary-sDejdrYe8cg.zh-CN.vtt 1.13 KB
Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.pt-BR.vtt 1.13 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.en.vtt 1.13 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.pt-BR.vtt 1.13 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.en.vtt 1.13 KB
Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.pt-BR.vtt 1.13 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-kJ4Y8a1rOkY.zh-CN.vtt 1.13 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.pt-BR.vtt 1.13 KB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.ja.vtt 1.13 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/33. Adding Bars and Text-EcwO8YPrn-M.zh-CN.vtt 1.13 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.pt-BR.vtt 1.13 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/12. Data-d7aERRVkccY.zh-CN.vtt 1.13 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/12. Data-d7aERRVkccY.zh-CN.vtt 1.13 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.pt-BR.vtt 1.13 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.zh-CN.vtt 1.13 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/22. Clean Code 2 Solution-ncqhpqt0Mik.zh-CN.vtt 1.13 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.en.vtt 1.12 KB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.ja.vtt 1.12 KB
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.hr.vtt 1.12 KB
Part 17-Module 01-Lesson 16_Logistic Regression/31. Final Thoughts On Shifting To Machine Learning-YkZFjZ3Fx8A.zh-CN.vtt 1.12 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.pt-BR.vtt 1.12 KB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.en.vtt 1.12 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.es.vtt 1.12 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.es.vtt 1.12 KB
Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.en.vtt 1.12 KB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.en.vtt 1.12 KB
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.ar.vtt 1.12 KB
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.pt-BR.vtt 1.12 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/11. In-Place vs. Not In-Place-TVyv8acRPrs.zh-CN.vtt 1.12 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.ar.vtt 1.12 KB
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Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.ja.vtt 1.12 KB
Part 13-Module 01-Lesson 07_Narrative Structures/23. Analyzing Narrative Structures-xgm7DYBijo0.zh-CN.vtt 1.12 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.en.vtt 1.12 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/12. In-Place vs. Not In-Place-TVyv8acRPrs.zh-CN.vtt 1.12 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.ar.vtt 1.12 KB
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Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.ja.vtt 1.12 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.pt-BR.vtt 1.12 KB
Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.pt-BR.vtt 1.12 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/04. 02 Joining Tables-vSjKBMgW1Fw.zh-CN.vtt 1.12 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.en.vtt 1.12 KB
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.ar.vtt 1.12 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.pt-BR.vtt 1.12 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.ar.vtt 1.12 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.pt-BR.vtt 1.12 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.pt-BR.vtt 1.12 KB
Part 05-Module 02-Lesson 03_Elements of SQL/08. The Experiment Page--GlHaeB-vic.zh-CN.vtt 1.12 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.en.vtt 1.12 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.en.vtt 1.12 KB
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.ar.vtt 1.12 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.it.vtt 1.12 KB
Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.en.vtt 1.12 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.pt-BR.vtt 1.12 KB
Part 18-Module 03-Lesson 01_Assessing Data/16. Quality Programatic Assessment 2 -Ngl_TsqhMsc.zh-CN.vtt 1.12 KB
Part 21-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.zh-CN.vtt 1.12 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.pt-BR.vtt 1.12 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.en.vtt 1.12 KB
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.pt-BR.vtt 1.11 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.ko.vtt 1.11 KB
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.zh-CN.vtt 1.11 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.pt-BR.vtt 1.11 KB
Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.pt-BR.vtt 1.11 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.hr.vtt 1.11 KB
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.en.vtt 1.11 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.pt-BR.vtt 1.11 KB
Part 16-Module 03-Lesson 02_SQL Joins/10. ALIAS-viWHJaxWTvw.zh-CN.vtt 1.11 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.it.vtt 1.11 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean--boAkUs-amM.zh-CN.vtt 1.11 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.pt-BR.vtt 1.11 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.ar.vtt 1.11 KB
Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.en.vtt 1.11 KB
Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.pt-BR.vtt 1.11 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.ar.vtt 1.11 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.pt-BR.vtt 1.11 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.pt-BR.vtt 1.11 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.en.vtt 1.11 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.es-ES.vtt 1.11 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.pt-BR.vtt 1.11 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/16. Exploring JSON-kT0jBsXOouw.zh-CN.vtt 1.11 KB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.ar.vtt 1.11 KB
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/02. Data Overview-V-iPdJfrscQ.zh-CN.vtt 1.11 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.pt-BR.vtt 1.11 KB
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.en.vtt 1.11 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/15. Sets and groups with Trina-I59eqlvfMZk.zh-CN.vtt 1.11 KB
Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.en.vtt 1.11 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.pt-BR.vtt 1.11 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.pt-BR.vtt 1.11 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.pt-BR.vtt 1.11 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-bLDBg86nm6o.zh-CN.vtt 1.11 KB
Part 05-Module 02-Lesson 01_Data and Tables/04. Data Types and Meaning-Bb2K_pql26Y.zh-CN.vtt 1.11 KB
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.ja.vtt 1.11 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.es.vtt 1.11 KB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.pt-BR.vtt 1.11 KB
Part 09-Module 01-Lesson 02_R Basics/11. R Markdown Documents-oBns-s2TDgI.zh-CN.vtt 1.11 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.pt-BR.vtt 1.11 KB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.pt-BR.vtt 1.11 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.es-ES.vtt 1.11 KB
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.en.vtt 1.1 KB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-sbQXPn9xLvI.zh-CN.vtt 1.1 KB
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.ar.vtt 1.1 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-lEl0alktZkM.zh-CN.vtt 1.1 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-lEl0alktZkM.zh-CN.vtt 1.1 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-ZywJPwlHuh8.zh-CN.vtt 1.1 KB
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.ar.vtt 1.1 KB
Part 11-Module 01-Lesson 10_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.zh-CN.vtt 1.1 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.en.vtt 1.1 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.zh-CN.vtt 1.1 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.en.vtt 1.1 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.en.vtt 1.1 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.en.vtt 1.1 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.en.vtt 1.1 KB
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.ar.vtt 1.1 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.ja.vtt 1.1 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution-GNAZ2S3igr4.en.vtt 1.1 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.en.vtt 1.1 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.en.vtt 1.1 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-oERHYF9QCkY.zh-CN.vtt 1.1 KB
Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.en.vtt 1.1 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.en.vtt 1.1 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/05. More AB Testing Possibilities-rGw4xFsUUqE.zh-CN.vtt 1.1 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.ja.vtt 1.1 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.en.vtt 1.1 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.es.vtt 1.1 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.en.vtt 1.1 KB
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.en.vtt 1.1 KB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.pt-BR.vtt 1.1 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.pt-BR.vtt 1.1 KB
Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.pt-BR.vtt 1.1 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/11. DataFrame applymap()-Vp43h6ZRyoQ.zh-CN.vtt 1.1 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.pt-BR.vtt 1.1 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/11. DataFrame applymap()-Vp43h6ZRyoQ.zh-CN.vtt 1.1 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.en.vtt 1.1 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/12. Affect t-Statistic-HMfd6rQrI0Y.zh-CN.vtt 1.1 KB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.ja.vtt 1.1 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.ja.vtt 1.1 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.pt-BR.vtt 1.1 KB
Part 18-Module 02-Lesson 01_Gathering Data/27. Conclusion-IanoSiET2nA.zh-CN.vtt 1.1 KB
Part 21-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.zh-CN.vtt 1.1 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.en.vtt 1.09 KB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.pt-BR.vtt 1.09 KB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.zh-CN.vtt 1.09 KB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.pt-BR.vtt 1.09 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.es-ES.vtt 1.09 KB
Part 11-Module 01-Lesson 07_Regressions/21. Linear Regression Errors-A4nPMEOcUd4.zh-CN.vtt 1.09 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.pt-BR.vtt 1.09 KB
Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.pt-BR.vtt 1.09 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.ar.vtt 1.09 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.pt-BR.vtt 1.09 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.pt-BR.vtt 1.09 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.en.vtt 1.09 KB
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.pt-BR.vtt 1.09 KB
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/03. What is the Difference-I3tQvrCgNrQ.zh-CN.vtt 1.09 KB
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.ar.vtt 1.09 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.en.vtt 1.09 KB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.en.vtt 1.09 KB
Part 11-Module 01-Lesson 11_Text Learning/05. Properties of Bag of Words-3r8OR2yQ-KI.zh-CN.vtt 1.09 KB
Part 12-Module 01-Lesson 04_Land a Job Offer/01. Land a Job Offer-ZQJoT8QL_hw.zh-CN.vtt 1.09 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.en.vtt 1.09 KB
Part 18-Module 03-Lesson 01_Assessing Data/22. Outro -lfWT0kLfe8c.zh-CN.vtt 1.09 KB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.ar.vtt 1.09 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.en.vtt 1.09 KB
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Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.en.vtt 1.09 KB
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Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-gzu9UcNF0_k.zh-CN.vtt 1.09 KB
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Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-ZO7y9tsSQ0A.zh-CN.vtt 1.09 KB
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Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.en.vtt 1.08 KB
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Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.it.vtt 1.08 KB
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Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.th.vtt 1.08 KB
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Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.es.vtt 1.08 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.en.vtt 1.08 KB
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Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.en.vtt 1.08 KB
Part 11-Module 01-Lesson 02_Naive Bayes/03. Supervised Classification Example-buxApBhZCO0.zh-CN.vtt 1.08 KB
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Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.ja.vtt 1.08 KB
Part 21-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.zh-CN.vtt 1.08 KB
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Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.zh-CN.vtt 1.08 KB
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Part 03-Module 01-Lesson 04_L2 Visualizing Data/11. Number of Rows-zxeKDuSK31M.zh-CN.vtt 1.08 KB
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.en.vtt 1.08 KB
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Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.pt-BR.vtt 1.08 KB
Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.en.vtt 1.08 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/17. Plotting in Pandas-ujJShz9YfAU.zh-CN.vtt 1.08 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-TU63rBOwXQ8.zh-CN.vtt 1.08 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.ar.vtt 1.08 KB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.zh-CN.vtt 1.08 KB
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.pt-BR.vtt 1.08 KB
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.ja.vtt 1.08 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/14. 141 Assess Intro V4-mdrAdtziXh4.en.vtt 1.08 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/18. Plotting in Pandas-ujJShz9YfAU.zh-CN.vtt 1.08 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.es.vtt 1.08 KB
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.en.vtt 1.08 KB
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.ar.vtt 1.08 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.ar.vtt 1.07 KB
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.ar.vtt 1.07 KB
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.ja.vtt 1.07 KB
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.en.vtt 1.07 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-6Z3BJWRuOAE.zh-CN.vtt 1.07 KB
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.ar.vtt 1.07 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.pt-BR.vtt 1.07 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.pt-BR.vtt 1.07 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.en.vtt 1.07 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.zh-CN.vtt 1.07 KB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.pt-BR.vtt 1.07 KB
Part 12-Module 02-Lesson 02_List-Based Collections/08. Stacks-DQoCO8aGcNc.zh-CN.vtt 1.07 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-mPN46IqnT1c.zh-CN.vtt 1.07 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.en.vtt 1.07 KB
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.ar.vtt 1.07 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.en.vtt 1.07 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.en.vtt 1.07 KB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.pt-BR.vtt 1.07 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.pt-BR.vtt 1.07 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.pt-BR.vtt 1.07 KB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.en-US.vtt 1.07 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/15. Properties of the Mean-uSXJtEpwEVM.zh-CN.vtt 1.07 KB
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.pt-BR.vtt 1.07 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-fdylxSVOsnw.zh-CN.vtt 1.07 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.pt-BR.vtt 1.07 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.ar.vtt 1.07 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.en.vtt 1.07 KB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.en.vtt 1.07 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.ar.vtt 1.07 KB
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.en.vtt 1.07 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.es-ES.vtt 1.07 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.ar.vtt 1.07 KB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.en.vtt 1.07 KB
Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.pt-BR.vtt 1.07 KB
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-1GCPKAYDPTg.zh-CN.vtt 1.07 KB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.en.vtt 1.07 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.pt-BR.vtt 1.06 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.pt-BR.vtt 1.06 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.pt-BR.vtt 1.06 KB
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/09. Pandas Axis Names-8vr8KQuJLcQ.zh-CN.vtt 1.06 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.ja.vtt 1.06 KB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.zh-CN.vtt 1.06 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/29. Conclusion-SRXNBlvW-xw.zh-CN.vtt 1.06 KB
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/09. Pandas Axis Names-8vr8KQuJLcQ.zh-CN.vtt 1.06 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.en.vtt 1.06 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.en.vtt 1.06 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.en.vtt 1.06 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.ja.vtt 1.06 KB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.en-US.vtt 1.06 KB
Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.en.vtt 1.06 KB
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.ja.vtt 1.06 KB
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.en.vtt 1.06 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/41. The World Cup Narrative-nnqZR2GdcAA.zh-CN.vtt 1.06 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.ar.vtt 1.06 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.en.vtt 1.06 KB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.ar.vtt 1.06 KB
Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.en.vtt 1.06 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.en.vtt 1.06 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.en.vtt 1.06 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.en.vtt 1.06 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.ja.vtt 1.06 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.pt-BR.vtt 1.06 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.en.vtt 1.06 KB
Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.pt-BR.vtt 1.06 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.en-US.vtt 1.06 KB
Part 17-Module 01-Lesson 13_Case Study AB tests/16. Drawing Conclusions-s-4ghG9vrGQ.zh-CN.vtt 1.06 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.pt-BR.vtt 1.06 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-OVeEr0CSe8U.zh-CN.vtt 1.06 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.en.vtt 1.06 KB
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.en.vtt 1.06 KB
Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.en.vtt 1.06 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.ja.vtt 1.06 KB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.ar.vtt 1.06 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.en.vtt 1.06 KB
Part 14-Module 01-Lesson 01_Overview of AB Testing/16. Establishing Statistical Significance-C22VZ_mY5RM.zh-CN.vtt 1.06 KB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.pt-BR.vtt 1.06 KB
Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.en.vtt 1.06 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.pt-BR.vtt 1.06 KB
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ar.vtt 1.06 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.zh-CN.vtt 1.06 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-GF0qAvNKpOA.zh-CN.vtt 1.05 KB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.en.vtt 1.05 KB
Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.en-US.vtt 1.05 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/19. D3 Scales-pFRoUknUJl8.zh-CN.vtt 1.05 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.zh-CN.vtt 1.05 KB
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.ar.vtt 1.05 KB
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/10. 27. English Teaching-HmsNljRIsr4.zh-CN.vtt 1.05 KB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.ja.vtt 1.05 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.en.vtt 1.05 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.zh-CN.vtt 1.05 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.zh-CN.vtt 1.05 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-Vx9bxJHQJf8.zh-CN.vtt 1.05 KB
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-imNv6Q8GiQM.zh-CN.vtt 1.05 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.en.vtt 1.05 KB
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings-0-LYyC_70jk.zh-CN.vtt 1.05 KB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.pt-BR.vtt 1.05 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.ar.vtt 1.05 KB
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.ar.vtt 1.05 KB
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.pt-BR.vtt 1.05 KB
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.ko.vtt 1.05 KB
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-gg7SAMMl4kM.zh-CN.vtt 1.05 KB
Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.en.vtt 1.05 KB
Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.en.vtt 1.05 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-CLgVLQAEYw8.hr.vtt 1.05 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/09. Combining Data-7KICenO-lKc.zh-CN.vtt 1.05 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.en.vtt 1.05 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.en.vtt 1.05 KB
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Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.pt-BR.vtt 1.05 KB
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.en.vtt 1.05 KB
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.ar.vtt 1.05 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.en.vtt 1.05 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.en.vtt 1.05 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.pt-BR.vtt 1.05 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ar.vtt 1.05 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.pt-BR.vtt 1.05 KB
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.pt-BR.vtt 1.05 KB
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-vsqelq1aYy8.zh-CN.vtt 1.05 KB
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.ar.vtt 1.05 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.pt-BR.vtt 1.05 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/03. Projects and Progress-Z9ZLMQWsbsk.zh-CN.vtt 1.05 KB
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.pt-BR.vtt 1.05 KB
Part 11-Module 01-Lesson 04_Decision Trees/03. Multiple Linear Questions-t1Y-nzgI1L4.zh-CN.vtt 1.05 KB
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.pt-BR.vtt 1.05 KB
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.ar.vtt 1.05 KB
Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.pt-BR.vtt 1.05 KB
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.pt-BR.vtt 1.05 KB
Part 18-Module 02-Lesson 01_Gathering Data/09. HTML File Structure -4ef_Dr_SXTw.zh-CN.vtt 1.05 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.es.vtt 1.05 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.en.vtt 1.05 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.pt-BR.vtt 1.05 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.ar.vtt 1.05 KB
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.ar.vtt 1.05 KB
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.pt-BR.vtt 1.05 KB
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.ja.vtt 1.05 KB
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.en.vtt 1.05 KB
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.pt-BR.vtt 1.05 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.en.vtt 1.04 KB
Part 18-Module 04-Lesson 01_Cleaning Data/05. Data Cleaning Process -BS_p9kwMEMk.zh-CN.vtt 1.04 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.en.vtt 1.04 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.pt-BR.vtt 1.04 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.pt-BR.vtt 1.04 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-LOwWWIXvnhU.zh-CN.vtt 1.04 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.en.vtt 1.04 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.ar.vtt 1.04 KB
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-FpeMuGuo74k.zh-CN.vtt 1.04 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.pt-BR.vtt 1.04 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.en.vtt 1.04 KB
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-ICUYxC-8d7o.en.vtt 1.04 KB
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.pt-BR.vtt 1.04 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.zh-CN.vtt 1.04 KB
Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.en.vtt 1.04 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/02. One Number to Describe Data-6QfvhQ0En0E.zh-CN.vtt 1.04 KB
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.en.vtt 1.04 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.pt-BR.vtt 1.04 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/19. World Cup Top Scorers-TBJY7UsKtYU.zh-CN.vtt 1.04 KB
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.ar.vtt 1.04 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.en.vtt 1.04 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.en.vtt 1.04 KB
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.ar.vtt 1.04 KB
Part 13-Module 01-Lesson 04_Design Principles/05. Visualizations in Data Science-UCKGGQ4LFjo.zh-CN.vtt 1.04 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.en.vtt 1.04 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download II-T4iFJoHb_qU.zh-CN.vtt 1.04 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.en.vtt 1.04 KB
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.pt-BR.vtt 1.04 KB
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.ja.vtt 1.04 KB
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.th.vtt 1.04 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.pt-BR.vtt 1.04 KB
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.en.vtt 1.04 KB
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-31yCnTUNzts.zh-CN.vtt 1.04 KB
Part 13-Module 01-Lesson 07_Narrative Structures/08. How to Lie with Pie Charts-q-EjlMl1Bj4.zh-CN.vtt 1.04 KB
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.pt-BR.vtt 1.04 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/18. UNC-Ko-g24l1LpQ.zh-CN.vtt 1.04 KB
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.ar.vtt 1.04 KB
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-JsFlZfNpVl4.zh-CN.vtt 1.04 KB
Part 13-Module 01-Lesson 05_Dimple.js/14. Adding a Series with Dimple-clyCsNwceP0.zh-CN.vtt 1.04 KB
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.pt-BR.vtt 1.04 KB
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.en.vtt 1.04 KB
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.en.vtt 1.04 KB
Part 09-Module 01-Lesson 02_R Basics/07. RStudio Layout-LcHWlS84sao.zh-CN.vtt 1.04 KB
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.en.vtt 1.04 KB
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-jOxS1eJRsOk.zh-CN.vtt 1.04 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.pt-BR.vtt 1.04 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.en.vtt 1.04 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.ar.vtt 1.04 KB
Part 01-Module 01-Lesson 01_Nanodegree Orientation/09. How Does Project Submission Work-jCJa_VP6qgg.zh-CN.vtt 1.03 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.en.vtt 1.03 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-Zw3X9BQQKB0.zh-CN.vtt 1.03 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.zh-CN.vtt 1.03 KB
Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.en.vtt 1.03 KB
Part 12-Module 02-Lesson 06_Graphs/01. Graph Introduction-DFR8F2Q9lgo.pt-BR.vtt 1.03 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.zh-CN.vtt 1.03 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.pt-BR.vtt 1.03 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.pt-BR.vtt 1.03 KB
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.ar.vtt 1.03 KB
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.ja.vtt 1.03 KB
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.ar.vtt 1.03 KB
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/03. Choose Your Own Adventure-Ka9nwD0QzTI.zh-CN.vtt 1.03 KB
Part 11-Module 01-Lesson 09_Clustering/17. Clustering Mini-Project Video-68EGMItJiNM.en.vtt 1.03 KB
Part 18-Module 02-Lesson 01_Gathering Data/12. Source Downloading Files From The Internet II-M0qR7to1fl4.en.vtt 1.03 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-oR8H9vdtreE.zh-CN.vtt 1.03 KB
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.pt-BR.vtt 1.03 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.en.vtt 1.03 KB
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.en.vtt 1.03 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/10. Theoretical Normal Distribution-vyy5yUt1IrE.zh-CN.vtt 1.03 KB
Part 13-Module 01-Lesson 05_Dimple.js/10. Dimple Axes, Series and Fields-nSqsoDChbEU.zh-CN.vtt 1.03 KB
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.ar.vtt 1.03 KB
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.pt-BR.vtt 1.03 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-Uf_KdjVT2Xg.zh-CN.vtt 1.03 KB
Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.pt-BR.vtt 1.03 KB
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-Uf_KdjVT2Xg.zh-CN.vtt 1.03 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.pt-BR.vtt 1.03 KB
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.pt-BR.vtt 1.03 KB
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.pt-BR.vtt 1.03 KB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.en-US.vtt 1.03 KB
Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.en-US.vtt 1.03 KB
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.pt-BR.vtt 1.03 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.en.vtt 1.03 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.en.vtt 1.03 KB
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.en.vtt 1.03 KB
Part 09-Module 01-Lesson 02_R Basics/13. Ordered Factors-Mbd1jfsbvik.zh-CN.vtt 1.03 KB
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.ar.vtt 1.03 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.pt-BR.vtt 1.03 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.en.vtt 1.03 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.pt-BR.vtt 1.03 KB
Part 11-Module 01-Lesson 02_Naive Bayes/20. Calculating NB Accuracy-m989etSymQQ.zh-CN.vtt 1.03 KB
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-yD9C03vqNeI.zh-CN.vtt 1.03 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.es.vtt 1.02 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.es.vtt 1.02 KB
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.pt-BR.vtt 1.02 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.ja.vtt 1.02 KB
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.ar.vtt 1.02 KB
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.ar.vtt 1.02 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.en.vtt 1.02 KB
Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.en.vtt 1.02 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.zh-CN.vtt 1.02 KB
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.en.vtt 1.02 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.pt-BR.vtt 1.02 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.es.vtt 1.02 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.es.vtt 1.02 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.es.vtt 1.02 KB
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-CBaw2pGOO3A.zh-CN.vtt 1.02 KB
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/30. Hot Beverage-r-TWqzDJZJs.zh-CN.vtt 1.02 KB
Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.en.vtt 1.02 KB
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.en.vtt 1.02 KB
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.en.vtt 1.02 KB
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.en.vtt 1.02 KB
Part 12-Module 02-Lesson 04_Maps and Hashing/01. Introduction to Maps-JEw3iQAnGKQ.zh-CN.vtt 1.02 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/02. Technical Interlude-QWA06Ro4ix0.zh-CN.vtt 1.02 KB
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.ar.vtt 1.02 KB
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.ar.vtt 1.02 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.es.vtt 1.02 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.en.vtt 1.02 KB
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.en.vtt 1.02 KB
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.pt-BR.vtt 1.02 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.es.vtt 1.02 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.es.vtt 1.02 KB
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.pt-BR.vtt 1.02 KB
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-rS6udGwrN90.zh-CN.vtt 1.02 KB
Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.en.vtt 1.02 KB
Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.es-MX.vtt 1.02 KB
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.pt-BR.vtt 1.02 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.pt-BR.vtt 1.02 KB
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.en.vtt 1.02 KB
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/21. What's Next-AwpX6HkhL0k.zh-CN.vtt 1.02 KB
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.pt-BR.vtt 1.02 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.pt-BR.vtt 1.02 KB
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.pt-BR.vtt 1.02 KB
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-xU84TShi7I4.pt-BR.vtt 1.02 KB
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.ar.vtt 1.02 KB
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.pt-BR.vtt 1.02 KB
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.ar.vtt 1.02 KB
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.pt-BR.vtt 1.02 KB
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.ar.vtt 1.02 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.es.vtt 1.01 KB
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.es.vtt 1.01 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.pt-BR.vtt 1.01 KB
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-5j6VZr8sHo8.zh-CN.vtt 1.01 KB
Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.en.vtt 1.01 KB
Part 14-Module 01-Lesson 05_Analyzing Results/06. Checking Invariants, Part 2-Mftti4FSjn4.zh-CN.vtt 1.01 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/05. Vectorized Operations--InZYjwPsKs.pt-BR.vtt 1.01 KB
Part 17-Module 01-Lesson 15_Multiple Linear Regression/20. Interactions And Higher Order Terms-AOfXMiJgo48.zh-CN.vtt 1.01 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/06. Vectorized Operations--InZYjwPsKs.pt-BR.vtt 1.01 KB
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.en.vtt 1.01 KB
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.ar.vtt 1.01 KB
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.pt-BR.vtt 1.01 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/15. Assess Visual-PVbOzw5libM.en.vtt 1.01 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.pt-BR.vtt 1.01 KB
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.ar.vtt 1.01 KB
Part 12-Module 02-Lesson 06_Graphs/09. Graph Traversal-Dkt-XxHZaZE.zh-CN.vtt 1.01 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.pt-BR.vtt 1.01 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.en.vtt 1.01 KB
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-DM1zSW5aoCc.zh-CN.vtt 1.01 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.en.vtt 1.01 KB
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.ar.vtt 1.01 KB
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.ar.vtt 1.01 KB
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-W5qXCZ-nrHM.zh-CN.vtt 1.01 KB
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.en.vtt 1.01 KB
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.en.vtt 1.01 KB
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.zh-Hans.vtt 1.01 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-3uUwfgOUT0Y.zh-CN.vtt 1.01 KB
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.pt-BR.vtt 1.01 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.ja.vtt 1.01 KB
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.ar.vtt 1.01 KB
Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.pt-BR.vtt 1.01 KB
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.pt-BR.vtt 1.01 KB
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.pt-BR.vtt 1.01 KB
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/32. Keyboards-0m5k7Ni1O48.zh-CN.vtt 1.01 KB
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.pt-BR.vtt 1.01 KB
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.en.vtt 1.01 KB
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.ar.vtt 1.01 KB
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.en.vtt 1.01 KB
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.ar.vtt 1.01 KB
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.pt-BR.vtt 1.01 KB
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.en-US.vtt 1 KB
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.en.vtt 1 KB
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ar.vtt 1 KB
Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.en.vtt 1 KB
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.ja.vtt 1 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.en.vtt 1 KB
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.zh-CN.vtt 1 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-Ur01espw7ko.zh-CN.vtt 1 KB
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.ar.vtt 1 KB
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.ar.vtt 1 KB
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.pt-BR.vtt 1 KB
Part 04-Module 02-Lesson 01_Data Analysis Process/08. Questions about Student Data-AO8vSyAtfV4.zh-CN.vtt 1 KB
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.ar.vtt 1 KB
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.pt-BR.vtt 1 KB
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-7LGaeYfvRug.zh-CN.vtt 1 KB
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.zh-CN.vtt 1 KB
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/07. Difficult Metrics-kutWDS1chik.zh-CN.vtt 1 KB
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.en.vtt 1 KB
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.pt-BR.vtt 1 KB
Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.en-US.vtt 1 KB
Part 13-Module 01-Lesson 07_Narrative Structures/37. Visualize Every Game of the World Cup-fxgnL-Lv684.zh-CN.vtt 1 KB
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.th.vtt 1 KB
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.zh-CN.vtt 1023 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-0aDtHA_lGc8.zh-CN.vtt 1023 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-CoFbRt4icdQ.zh-CN.vtt 1023 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.ar.vtt 1023 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/17. Why Data Dashboards-8ni2lCqAVvQ.zh-CN.vtt 1022 B
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.en.vtt 1021 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.en.vtt 1021 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.pt-BR.vtt 1021 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.th.vtt 1021 B
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.pt-BR.vtt 1021 B
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -adqc5fF5B8Y.pt-BR.vtt 1020 B
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.ar.vtt 1020 B
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.en.vtt 1020 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.pt-BR.vtt 1019 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.pt-BR.vtt 1019 B
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.pt-BR.vtt 1019 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.ar.vtt 1019 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.en.vtt 1018 B
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.pt-BR.vtt 1018 B
Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.zh-CN.vtt 1018 B
Part 13-Module 01-Lesson 05_Dimple.js/35. What's Next-mKJkmv7h9ro.zh-CN.vtt 1018 B
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.ja.vtt 1018 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.pt-BR.vtt 1017 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.pt-BR.vtt 1017 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.en.vtt 1017 B
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.pt-BR.vtt 1016 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.ar.vtt 1016 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.ar.vtt 1016 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.pt-BR.vtt 1016 B
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.en.vtt 1015 B
Part 16-Module 03-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.zh-CN.vtt 1015 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.th.vtt 1015 B
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.en.vtt 1014 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-_kADa-a_UD8.zh-CN.vtt 1014 B
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.pt-BR.vtt 1014 B
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-0QiU3p8POHk.zh-CN.vtt 1014 B
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.pt-BR.vtt 1014 B
Part 17-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.zh-CN.vtt 1014 B
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.en.vtt 1013 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/22. Find P-Value-pwQ7IQgremk.zh-CN.vtt 1013 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.en.vtt 1013 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.en.vtt 1013 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.en.vtt 1012 B
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-5zoL8YdM6sI.zh-CN.vtt 1012 B
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-mzKPXz-Yhwk.zh-CN.vtt 1012 B
Part 11-Module 01-Lesson 14_Validation/08. K-Fold Cross Validation-ADNFKiAjmWA.zh-CN.vtt 1012 B
Part 13-Module 01-Lesson 05_Dimple.js/18. Adding the Y-axis-22JU1uui9y4.zh-CN.vtt 1012 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.pt-BR.vtt 1012 B
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.en.vtt 1012 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-YNuoRW6EyEo.zh-CN.vtt 1011 B
Part 12-Module 02-Lesson 08_Technical Interview - Python/10. Interview Wrap-Up-sz4Ekcu9a_Q.pt-BR.vtt 1011 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/21. Conclusion-JUI9VHvwI08.zh-CN.vtt 1010 B
Part 11-Module 01-Lesson 07_Regressions/33. What Data Is Good For Linear Regression-KFVdS328iC8.zh-CN.vtt 1010 B
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.en.vtt 1010 B
Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.en.vtt 1010 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.it.vtt 1010 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/21. Conclusion-JUI9VHvwI08.zh-CN.vtt 1010 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.pt-BR.vtt 1009 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.pt-BR.vtt 1009 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.ar.vtt 1009 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.pt-BR.vtt 1008 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.ar.vtt 1008 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.en.vtt 1008 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.ar.vtt 1008 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.en.vtt 1008 B
Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.en.vtt 1008 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.pt-BR.vtt 1007 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.pt-BR.vtt 1007 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.pt-BR.vtt 1007 B
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-vjnKnaZa43M.pt-BR.vtt 1007 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.en-US.vtt 1007 B
Part 21-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.zh-CN.vtt 1007 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.pt-BR.vtt 1007 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.en.vtt 1006 B
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.ar.vtt 1006 B
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.pt-BR.vtt 1006 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.ar.vtt 1006 B
Part 03-Module 01-Lesson 20_L8 Estimation/33. Wrap-Up-6iSCMFK3EYc.zh-CN.vtt 1005 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.en.vtt 1005 B
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.ja.vtt 1005 B
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.en.vtt 1005 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.en.vtt 1005 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/22. Conduct Hypothesis Test-EeI8F1_7zbQ.zh-CN.vtt 1004 B
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-6BBUSWrSuFA.zh-CN.vtt 1004 B
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.pt-BR.vtt 1004 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.en.vtt 1004 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/08. Data Visualization and You-m_nSthII_IE.zh-CN.vtt 1004 B
Part 16-Module 03-Lesson 01_Basic SQL/27. WHERE with Non-Numeric Data-_pLx7MHOyjo.zh-CN.vtt 1004 B
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.zh-CN.vtt 1004 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.pt-BR.vtt 1003 B
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.pt-BR.vtt 1003 B
Part 11-Module 01-Lesson 14_Validation/02. Benefits of Testing-N6hiygoT9FE.zh-CN.vtt 1003 B
Part 16-Module 03-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.zh-CN.vtt 1003 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.es-ES.vtt 1003 B
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.pt-BR.vtt 1002 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.en.vtt 1002 B
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.pt-BR.vtt 1002 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.ar.vtt 1002 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-HVa4G8jQbEo.zh-CN.vtt 1001 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-HVa4G8jQbEo.zh-CN.vtt 1001 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.pt-BR.vtt 1001 B
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.pt-BR.vtt 1001 B
Part 11-Module 01-Lesson 03_SVM/20. Playing Around with Kernel Choices-sy_jiSEy-Nw.zh-CN.vtt 1001 B
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.ja.vtt 1001 B
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.en.vtt 1001 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.ja.vtt 1000 B
Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.en.vtt 1000 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.ar.vtt 1000 B
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.pt-BR.vtt 999 B
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.ja.vtt 999 B
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.ar.vtt 999 B
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-K-rQ8KnmmH8.zh-CN.vtt 999 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.ar.vtt 999 B
Part 03-Module 01-Lesson 13_L5 Standardizing/02. USCF Distribution-GNAZ2S3igr4.zh-CN.vtt 998 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.pt-BR.vtt 998 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.ar.vtt 998 B
Part 11-Module 01-Lesson 12_Feature Selection/04. Visualizing Your New Feature-Tp5WCAJiCRY.zh-CN.vtt 998 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.it.vtt 997 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.pt-BR.vtt 997 B
Part 13-Module 01-Lesson 07_Narrative Structures/65. Lesson 3 Recap-MmJ6fBojjiA.zh-CN.vtt 997 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.en.vtt 997 B
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -adqc5fF5B8Y.en.vtt 996 B
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.pt-BR.vtt 996 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/16. Precision and Recall-3vT0kSBCLdU.zh-CN.vtt 996 B
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.pt-BR.vtt 996 B
Part 17-Module 01-Lesson 16_Logistic Regression/20. Precision and Recall-3vT0kSBCLdU.zh-CN.vtt 996 B
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.en.vtt 995 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.en.vtt 995 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.es.vtt 994 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.pt-BR.vtt 994 B
Part 05-Module 02-Lesson 01_Data and Tables/09. Queries and Results-l_HFnHve3Ok.zh-CN.vtt 994 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-ClkOE3kdvLs.zh-CN.vtt 994 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.it.vtt 994 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-69je8wHh2mQ.zh-CN.vtt 994 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-7AGEhuipHl4.zh-CN.vtt 993 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.pt-BR.vtt 993 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.pt-BR.vtt 993 B
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.ja.vtt 993 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.en.vtt 993 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.pt-BR.vtt 993 B
Part 11-Module 01-Lesson 11_Text Learning/15. Text Learning Mini-Project Video-GJviz-sIq9w.zh-CN.vtt 993 B
Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.pt-BR.vtt 993 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.pt-BR.vtt 993 B
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.ar.vtt 992 B
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.pt-BR.vtt 991 B
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.ar.vtt 991 B
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.en.vtt 991 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.pt-BR.vtt 989 B
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.en.vtt 989 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.ja.vtt 989 B
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.pt-BR.vtt 989 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.pt-BR.vtt 989 B
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.pt-BR.vtt 988 B
Part 03-Module 01-Lesson 11_L4 Variability/34. Spreadsheet SD-gqXiI9v7h8A.zh-CN.vtt 988 B
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.en.vtt 988 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.en.vtt 988 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.pt-BR.vtt 988 B
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.en.vtt 987 B
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.pt-BR.vtt 987 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.pt-BR.vtt 987 B
Part 17-Module 01-Lesson 13_Case Study AB tests/09. Experiment II-fq4eO7CybA4.zh-CN.vtt 987 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.es.vtt 986 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median--XPrm7KcCdc.zh-CN.vtt 986 B
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.en.vtt 986 B
Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.pt-BR.vtt 986 B
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.en.vtt 986 B
Part 13-Module 01-Lesson 08_Animation and Interaction/42. Adding Interactivity-Z5nOpgKYYj4.zh-CN.vtt 986 B
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.en-US.vtt 985 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-X5GWgtZEsgc.zh-CN.vtt 985 B
Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.en.vtt 985 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.ko.vtt 984 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.pt-BR.vtt 984 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.en.vtt 984 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.ja.vtt 984 B
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.ja.vtt 983 B
Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.pt-BR.vtt 983 B
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.en.vtt 983 B
Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.pt-BR.vtt 983 B
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.pt-BR.vtt 982 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ar.vtt 982 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/11. Introduction To Notation-ISkBSUVH49M.zh-CN.vtt 982 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.es.vtt 981 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.es.vtt 981 B
Part 05-Module 02-Lesson 05_Deeper into SQL/15. Inserts in DB API-RfYFqGPxMQM.zh-CN.vtt 981 B
Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.en.vtt 980 B
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.en.vtt 980 B
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.pt-BR.vtt 980 B
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-pxaXkCjukGM.zh-CN.vtt 980 B
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.en.vtt 979 B
Part 16-Module 03-Lesson 01_Basic SQL/03. Entity Relationship Diagrams-YY2TAJLEINA.zh-CN.vtt 979 B
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.en.vtt 979 B
Part 18-Module 02-Lesson 01_Gathering Data/25. You Can Iterate-QsJqoJYhTiw.zh-CN.vtt 979 B
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.en.vtt 978 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.en.vtt 978 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.pt-BR.vtt 978 B
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.en.vtt 978 B
Part 17-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-FnNveASivMA.zh-CN.vtt 978 B
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.en.vtt 977 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.pt-BR.vtt 977 B
Part 11-Module 01-Lesson 04_Decision Trees/21. Information Gain-KYieR9y-ue4.zh-CN.vtt 976 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.ar.vtt 976 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-QBaNltqVj_0.zh-CN.vtt 976 B
Part 13-Module 01-Lesson 08_Animation and Interaction/44. Adding Events to Buttons-UXRemP4hIyw.zh-CN.vtt 976 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.en.vtt 976 B
Part 09-Module 01-Lesson 03_Explore One Variable/06. Estimating Your Audience Size-FfzVPWM5DZ8.zh-CN.vtt 975 B
Part 09-Module 01-Lesson 05_Explore Two Variables/15. Create Scatterplots--gIxCjLXCEs.zh-CN.vtt 975 B
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.es-MX.vtt 975 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.pt-BR.vtt 975 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.ar.vtt 975 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.es-ES.vtt 975 B
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.pt-BR.vtt 974 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.pt-BR.vtt 974 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ar.vtt 974 B
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.ja.vtt 973 B
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.ar.vtt 973 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.en.vtt 973 B
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.ar.vtt 973 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-veRRrAR2xF4.zh-CN.vtt 972 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-veRRrAR2xF4.zh-CN.vtt 972 B
Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.pt-BR.vtt 972 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.pt-BR.vtt 972 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.zh-CN.vtt 971 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-M1EgoHdFSaE.zh-CN.vtt 971 B
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.ja.vtt 971 B
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-m8d9J5w3axY.zh-CN.vtt 971 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.es-ES.vtt 971 B
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.en.vtt 970 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.pt-BR.vtt 970 B
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.en.vtt 970 B
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.pt-BR.vtt 970 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.th.vtt 970 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.pt-BR.vtt 969 B
Part 09-Module 01-Lesson 07_Explore Many Variables/19. Number of Purchases-rQT88sMuM_M.zh-CN.vtt 969 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.ar.vtt 969 B
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.pt-BR.vtt 969 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.it.vtt 969 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.pt-BR.vtt 969 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.en.vtt 969 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.en.vtt 968 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/10. + vs. +=-J9FWaCBXhIk.zh-CN.vtt 968 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/11. + vs. +=-J9FWaCBXhIk.zh-CN.vtt 968 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.en.vtt 967 B
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.ar.vtt 967 B
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.ar.vtt 967 B
Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.pt-BR.vtt 967 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.it.vtt 967 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.es-ES.vtt 967 B
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.en.vtt 966 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.ja.vtt 966 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.ja.vtt 966 B
Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.pt-BR.vtt 966 B
Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.zh-CN.vtt 966 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-lPrKmvckG4E.zh-CN.vtt 966 B
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.pt-BR.vtt 965 B
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.ar.vtt 965 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.en.vtt 965 B
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.ar.vtt 965 B
Part 12-Module 02-Lesson 05_Trees/10. Binary Search Trees-7-ZQrugO-Yc.zh-CN.vtt 965 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.ar.vtt 965 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.pt-BR.vtt 965 B
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.ar.vtt 964 B
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.en.vtt 964 B
Part 13-Module 01-Lesson 07_Narrative Structures/52. D3 Hides Complexity-iNXkYbkD3IU.zh-CN.vtt 964 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.zh-CN.vtt 964 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.en.vtt 964 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/14. Other Sampling Distributions-Bxl0DonzX8c.zh-CN.vtt 964 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.en.vtt 963 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.en.vtt 963 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-kTsQyHV_T5E.zh-CN.vtt 963 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.en.vtt 963 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.en.vtt 963 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.en.vtt 963 B
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.ar.vtt 963 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.en.vtt 963 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ar.vtt 963 B
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.pt-BR.vtt 963 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.en.vtt 963 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/16. 34. Landmines-8ScnVyC24s8.zh-CN.vtt 962 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/09. Z-Score-1xXceRXrsg8.zh-CN.vtt 962 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-R5Jgz8SaVqM.zh-CN.vtt 962 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.pt-BR.vtt 962 B
Part 11-Module 01-Lesson 02_Naive Bayes/24. Cancer Test-uHIZl6MCiPY.zh-CN.vtt 962 B
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.pt-BR.vtt 962 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.ar.vtt 962 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-yYqN9Mf4jqw.zh-CN.vtt 962 B
Part 17-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.pt-BR.vtt 962 B
Part 03-Module 01-Lesson 11_L4 Variability/16. Measure Variability-j5fGEYLUOD4.zh-CN.vtt 961 B
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.en.vtt 961 B
Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.pt-BR.vtt 960 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.en-US.vtt 960 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.pt-BR.vtt 959 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.pt-BR.vtt 959 B
Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.pt-BR.vtt 959 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.ar.vtt 959 B
Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.en.vtt 959 B
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.en.vtt 958 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.en.vtt 958 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.en.vtt 957 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.en.vtt 957 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-tef9eqI2SVY.zh-CN.vtt 957 B
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.ar.vtt 957 B
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.pt-BR.vtt 957 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.en.vtt 957 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.es-ES.vtt 957 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.hr.vtt 957 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.ja.vtt 957 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.es.vtt 956 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.es.vtt 956 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/12. Example Details-aR6Z7ggnjEY.zh-CN.vtt 956 B
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-N5T8ouw1SGc.zh-CN.vtt 956 B
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.en.vtt 956 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.hr.vtt 956 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.pt-BR.vtt 956 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.es.vtt 955 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.es.vtt 955 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.pt-BR.vtt 955 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.en.vtt 955 B
Part 04-Module 02-Lesson 01_Data Analysis Process/18. Debugging Data Analysis Code -ReoDup994zk.zh-CN.vtt 955 B
Part 13-Module 01-Lesson 04_Design Principles/30. Color Blind-mmw24xSEB3A.zh-CN.vtt 955 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.pt-BR.vtt 954 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.pt-BR.vtt 954 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/18. Comparing Two Samples-kaVG7U0rda8.zh-CN.vtt 954 B
Part 11-Module 01-Lesson 03_SVM/18. Practice Making a New Feature-ygveMIhCtDg.zh-CN.vtt 953 B
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.ja.vtt 953 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.en.vtt 953 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.pt-BR.vtt 953 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.en.vtt 953 B
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.ar.vtt 953 B
Part 03-Module 01-Lesson 11_L4 Variability/15. Problem with IQR-h5l2EP3DR-4.zh-CN.vtt 952 B
Part 04-Module 02-Lesson 01_Data Analysis Process/16. Indulge Curiosity-9HnRVGjqNqE.zh-CN.vtt 952 B
Part 05-Module 02-Lesson 05_Deeper into SQL/17. One Query, Not Two-n7v-y8UrVJ0.zh-CN.vtt 952 B
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.ja.vtt 952 B
Part 13-Module 01-Lesson 08_Animation and Interaction/32. Enter Update Exit-lmDLMOPOj5I.zh-CN.vtt 952 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/15. Calculating a Confidence Interval-T-QWVJtXHAs.zh-CN.vtt 952 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.ja.vtt 952 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.en.vtt 952 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.pt-BR.vtt 951 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.en.vtt 951 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.en.vtt 951 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/12. DataFrame apply()-aGEUhSRys8w.zh-CN.vtt 950 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.ar.vtt 950 B
Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.pt-BR.vtt 950 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.pt-BR.vtt 950 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.ja.vtt 950 B
Part 12-Module 02-Lesson 08_Technical Interview - Python/03. Confirming Inputs-8lPTOG1yLsg.pt-BR.vtt 950 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/12. DataFrame apply()-aGEUhSRys8w.zh-CN.vtt 950 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.ar.vtt 950 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.pt-BR.vtt 949 B
Part 17-Module 01-Lesson 04_Probability/01. Introduction to Probability-HeoQccoqfTk.zh-CN.vtt 949 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.ja.vtt 949 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.ar.vtt 948 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.es-ES.vtt 948 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.es-ES.vtt 948 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.pt-BR.vtt 947 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-nJlJ0vlTRUs.zh-CN.vtt 947 B
Part 09-Module 01-Lesson 02_R Basics/01. The Power of R-Ca0MWoH_ZMY.zh-CN.vtt 947 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.ja.vtt 947 B
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.ar.vtt 946 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/19. Randomness-KwmQDhUkLAE.zh-CN.vtt 945 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/19. Randomness-KwmQDhUkLAE.zh-CN.vtt 945 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.en.vtt 945 B
Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.en.vtt 945 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.en.vtt 945 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.it.vtt 945 B
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.ar.vtt 945 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/10. Two-Tailed Critical Values 0.05-VCdJJTk2Izk.zh-CN.vtt 944 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.ar.vtt 944 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.zh-CN.vtt 944 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.pt-BR.vtt 944 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.pt-BR.vtt 944 B
Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.en.vtt 944 B
Part 09-Module 01-Lesson 05_Explore Two Variables/18. More Caution with Correlation-sefN2vaxjSA.zh-CN.vtt 943 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.en.vtt 943 B
Part 05-Module 02-Lesson 03_Elements of SQL/01. SQL is for Elephants-BYAyquwZmdM.zh-CN.vtt 942 B
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.en.vtt 942 B
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-3jfQlMLyH2o.zh-CN.vtt 942 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.en-US.vtt 942 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.ar.vtt 942 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.hr.vtt 942 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.es.vtt 941 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.ar.vtt 941 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.zh-Hans.vtt 940 B
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.pt-BR.vtt 940 B
Part 09-Module 01-Lesson 07_Explore Many Variables/12. Plot the Grand Mean-tmdzYKNqDSs.zh-CN.vtt 940 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.ja.vtt 940 B
Part 13-Module 01-Lesson 07_Narrative Structures/57. Styling Home Games with D3 Code-pq31lSXEQl0.zh-CN.vtt 940 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.en.vtt 940 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.en.vtt 940 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.en.vtt 940 B
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.en.vtt 939 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.en.vtt 939 B
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.en.vtt 939 B
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-bHVPpomkUYs.zh-CN.vtt 938 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/03. Degrees of Freedom-ZXkeT8mN4lg.zh-CN.vtt 938 B
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.ar.vtt 938 B
Part 13-Module 01-Lesson 04_Design Principles/01. Lesson Overview-k5T30IHD8T8.zh-CN.vtt 938 B
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.ar.vtt 938 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.en.vtt 937 B
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.en.vtt 937 B
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.pt-BR.vtt 937 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.pt-BR.vtt 937 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.pt-BR.vtt 937 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.pt-BR.vtt 937 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.en.vtt 936 B
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.en.vtt 935 B
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-w-czJptEyBk.zh-CN.vtt 935 B
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.ja.vtt 935 B
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.zh-CN.vtt 935 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.pt-BR.vtt 935 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/07. Categorical Ordinal Nominal Data-k5bLaPGY2Vw.zh-CN.vtt 935 B
Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.pt-BR.vtt 935 B
Part 18-Module 04-Lesson 01_Cleaning Data/04. Manual Vs Programmatic Cleaning -AQFBVQy_HyY.zh-CN.vtt 935 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/13. Data Modeling in JSON--rnzkOofIv0.zh-CN.vtt 934 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.ar.vtt 934 B
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.en.vtt 934 B
Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.pt-BR.vtt 934 B
Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.en.vtt 933 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.ja.vtt 933 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.pt-BR.vtt 933 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.en.vtt 933 B
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-Bs-wLbPOAfs.zh-CN.vtt 932 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.pt-BR.vtt 932 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.pt-BR.vtt 931 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.pt-BR.vtt 931 B
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.en.vtt 931 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-iZYv1WdWwQo.zh-CN.vtt 931 B
Part 13-Module 01-Lesson 07_Narrative Structures/59. New Data Stories in the Graphic-9yKFn_R2c_U.zh-CN.vtt 931 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.en.vtt 931 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.es.vtt 930 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.es.vtt 930 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.ar.vtt 930 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.pt-BR.vtt 930 B
Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.en.vtt 930 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.pt-BR.vtt 930 B
Part 17-Module 01-Lesson 07_Bayes Rule/30. Sebastian At Home-TtmQ7YCw_1Y.zh-CN.vtt 930 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.pt-BR.vtt 930 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/11. Report Results Effect Size-jjByXJIiCLs.zh-CN.vtt 929 B
Part 04-Module 02-Lesson 01_Data Analysis Process/12. Checking for More Problem Records-Hv58aHpWvEE.zh-CN.vtt 929 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.en.vtt 929 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.pt-BR.vtt 928 B
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.pt-BR.vtt 928 B
Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.pt-BR.vtt 928 B
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.pt-BR.vtt 928 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.en.vtt 928 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.pt-BR.vtt 928 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.ar.vtt 928 B
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.en.vtt 927 B
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.ja.vtt 927 B
Part 12-Module 01-Lesson 03_Interview Fails/01. Interview Fails-FD6UNqMa0xc.zh-CN.vtt 927 B
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.ar.vtt 927 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/26. Why Are Sampling Distributions Important-aDFDOCJKoH0.zh-CN.vtt 927 B
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.ar.vtt 926 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.ar.vtt 926 B
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.pt-BR.vtt 926 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.pt-BR.vtt 925 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.en.vtt 925 B
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.pt-BR.vtt 925 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.hr.vtt 925 B
Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.zh-CN.vtt 925 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.pt-BR.vtt 925 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-XDfqzA6nkqk.zh-CN.vtt 924 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.pt-BR.vtt 924 B
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.en.vtt 924 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.ar.vtt 924 B
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.en.vtt 924 B
Part 11-Module 01-Lesson 07_Regressions/18. AgeNet Worth Regression in sklearn-5aghWw9eIAM.zh-CN.vtt 924 B
Part 11-Module 01-Lesson 09_Clustering/15. Counterintuitive Clusters-aveIz1JYeAg.zh-CN.vtt 924 B
Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.en.vtt 924 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.pt-BR.vtt 923 B
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.en.vtt 923 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/13. Manipulating DOM Nodes-RMUHrUa7HR0.zh-CN.vtt 923 B
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-CML5XbavX0w.zh-CN.vtt 923 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.ja.vtt 923 B
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.ar.vtt 921 B
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.ja.vtt 921 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.pt-BR.vtt 921 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-mIzPoh_kqw4.zh-CN.vtt 920 B
Part 03-Module 01-Lesson 11_L4 Variability/21. Be Happy and Get Rid of Negatives-_ULZYGI6LPQ.zh-CN.vtt 920 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.pt-BR.vtt 920 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.en.vtt 920 B
Part 13-Module 01-Lesson 04_Design Principles/23. Careful with Color-aKwXLGs0Rfs.zh-CN.vtt 920 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.ar.vtt 920 B
Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.en.vtt 919 B
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.ja.vtt 919 B
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.en.vtt 919 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.pt-BR.vtt 919 B
Part 03-Module 01-Lesson 13_L5 Standardizing/01. Chess-mCZxHNB1u4w.zh-CN.vtt 918 B
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.ja.vtt 917 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/05. Slope Graphs-32WHsQi1UWc.zh-CN.vtt 917 B
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.ar.vtt 917 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.pt-BR.vtt 917 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.en.vtt 916 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.en.vtt 916 B
Part 11-Module 01-Lesson 04_Decision Trees/11. Min Samples Split-Mt5TWGYacJs.pt-BR.vtt 916 B
Part 11-Module 01-Lesson 13_PCA/32. PCA Mini-Project Intro-rR68JXwKBxE.zh-CN.vtt 916 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.ar.vtt 916 B
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.pt-BR.vtt 916 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.ar.vtt 916 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.it.vtt 915 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.pt-BR.vtt 914 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-S4KbzIyEwV8.zh-CN.vtt 914 B
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.en.vtt 914 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.pt-BR.vtt 914 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.pt-BR.vtt 914 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.zh-CN.vtt 914 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.pt-BR.vtt 913 B
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.ja.vtt 913 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.pt-BR.vtt 913 B
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.en-US.vtt 913 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/03. What Is Coming Up-oDJsnQcCPr4.zh-CN.vtt 913 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-9I8ysrRlmbA.zh-CN.vtt 913 B
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.ja.vtt 912 B
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.ar.vtt 912 B
Part 14-Module 01-Lesson 05_Analyzing Results/20. Course Conclusion-6aBIwp3n7_8.pt-BR.vtt 912 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-gGgqTGZ9TKg.zh-CN.vtt 912 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.pt-BR.vtt 911 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.pt-BR.vtt 911 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.ja.vtt 911 B
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.en.vtt 910 B
Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.pt-BR.vtt 910 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.th.vtt 910 B
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.en.vtt 909 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.pt-BR.vtt 909 B
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.en.vtt 909 B
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-sCHCU42thsI.zh-CN.vtt 908 B
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.ja.vtt 908 B
Part 17-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.zh-CN.vtt 908 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.en.vtt 908 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.en.vtt 907 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.en.vtt 906 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.en.vtt 906 B
Part 17-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.en.vtt 906 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/13. Line Plots-GsaBT47pjgQ.zh-CN.vtt 906 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-admfaazbCnY.zh-CN.vtt 905 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.zh-CN.vtt 905 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.es.vtt 904 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.es.vtt 904 B
Part 03-Module 01-Lesson 20_L8 Estimation/07. Confidence Interval Bounds-WeS0ogG86nk.zh-CN.vtt 904 B
Part 05-Module 02-Lesson 03_Elements of SQL/12. INSERT-49B5hlxzTRc.zh-CN.vtt 904 B
Part 11-Module 01-Lesson 02_Naive Bayes/16. NB Decision Boundary in Python-pauohSxuCVs.zh-CN.vtt 904 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.pt-BR.vtt 904 B
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.pt-BR.vtt 903 B
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.pt-BR.vtt 903 B
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.ar.vtt 903 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ar.vtt 903 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.en.vtt 902 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.pt-BR.vtt 902 B
Part 11-Module 01-Lesson 03_SVM/22. SVM C Parameter-WVg5-vxQDm8.zh-CN.vtt 902 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.ar.vtt 902 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.ja.vtt 902 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.pt-BR.vtt 901 B
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.en.vtt 901 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.ja.vtt 901 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.pt-BR.vtt 901 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.pt-BR.vtt 900 B
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.pt-BR.vtt 900 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.ar.vtt 900 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.en.vtt 900 B
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.en-US.vtt 900 B
Part 12-Module 02-Lesson 08_Technical Interview - Python/06. Runtime Analysis-8bI9OgOB2qI.zh-CN.vtt 900 B
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.ar.vtt 900 B
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.pt-BR.vtt 900 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.ar.vtt 900 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-mOPFQlKBg2M.es-ES.vtt 900 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.en.vtt 900 B
Part 05-Module 01-Lesson 05_Data Quality/01. Introduction-JA7oIPaf9PM.zh-CN.vtt 899 B
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.ja.vtt 899 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/25. Welcome to the End of Evaluation Lesson-sgFfl-j_oCs.zh-CN.vtt 899 B
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-3nZ2FL7C3sU.zh-CN.vtt 899 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ar.vtt 899 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.pt-BR.vtt 899 B
Part 09-Module 01-Lesson 05_Explore Two Variables/07. Alpha and Jitter-0OkHWvkwCus.zh-CN.vtt 898 B
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.en.vtt 898 B
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.en.vtt 898 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.en.vtt 898 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/09. Extra Practice With Dashboards-Va2zNfnUC6o.zh-CN.vtt 898 B
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.en.vtt 897 B
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.en.vtt 897 B
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.pt-BR.vtt 897 B
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.en.vtt 897 B
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-n1EbdV_CTcc.zh-CN.vtt 897 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.zh-CN.vtt 896 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/30. Double Blind-wRmbFgwsvQU.zh-CN.vtt 896 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/15. Filling Missing Values--xVYQQHNNuM.zh-CN.vtt 896 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.pt-BR.vtt 896 B
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.en.vtt 896 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.ar.vtt 896 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.zh-CN.vtt 896 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/16. Filling Missing Values--xVYQQHNNuM.zh-CN.vtt 896 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/27. Skewed Distribution-6LgGDqQLpyc.zh-CN.vtt 895 B
Part 03-Module 01-Lesson 13_L5 Standardizing/19. Mean of Standardized Distribution-QjhQztBNz-Q.zh-CN.vtt 895 B
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.en.vtt 895 B
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.en.vtt 895 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.en-US.vtt 895 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.en.vtt 895 B
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.pt-BR.vtt 895 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.pt-BR.vtt 895 B
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.en.vtt 894 B
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.en.vtt 894 B
Part 13-Module 01-Lesson 05_Dimple.js/15. The Benefits of Dimple-PkCeV9KNiMg.zh-CN.vtt 894 B
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.ar.vtt 894 B
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.ar.vtt 893 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.en.vtt 893 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.pt-BR.vtt 893 B
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.en.vtt 893 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.pt-BR.vtt 893 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/01. Introduction to Data Cleaning-YTtH3NM2BX0.zh-CN.vtt 893 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.es.vtt 892 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.pt-BR.vtt 892 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.ar.vtt 892 B
Part 17-Module 01-Lesson 07_Bayes Rule/33. Bayes' Rule and Robotics-meNSO42JF6I.zh-CN.vtt 892 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.es.vtt 891 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.es.vtt 891 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/24. Final Thoughts-CNGDocH1k3k.zh-CN.vtt 891 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.pt-BR.vtt 891 B
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.ar.vtt 891 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.en.vtt 891 B
Part 18-Module 04-Lesson 01_Cleaning Data/14. Cleaning For Quallity -qyixEwMRtWA.en.vtt 891 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-NMnlSnu8DPI.zh-CN.vtt 890 B
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.en.vtt 890 B
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.pt-BR.vtt 890 B
Part 17-Module 01-Lesson 12_Hypothesis Testing/32. Hypothesis Testing Conclusion-nQFchD4XPPs.zh-CN.vtt 890 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.pt-BR.vtt 889 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.es.vtt 888 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.es.vtt 888 B
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.pt-BR.vtt 888 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.pt-BR.vtt 888 B
Part 09-Module 01-Lesson 03_Explore One Variable/10. Moira's Outlier-vxS-Kh4eI0U.zh-CN.vtt 888 B
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.ar.vtt 888 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-8QEAYYIyopY.zh-CN.vtt 888 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.en.vtt 888 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-8QEAYYIyopY.zh-CN.vtt 888 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.pt-BR.vtt 887 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.pt-BR.vtt 887 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.en.vtt 887 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.en.vtt 887 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-tjEua8efugg.zh-CN.vtt 887 B
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.ar.vtt 887 B
Part 13-Module 01-Lesson 08_Animation and Interaction/16. Aggregating Data-aW9OOZKfqR8.zh-CN.vtt 887 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.ja.vtt 887 B
Part 17-Module 01-Lesson 12_Hypothesis Testing/16. How Do We Choose Between Hypotheses-JkXTwS-5Daw.zh-CN.vtt 887 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.pt-BR.vtt 886 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.es.vtt 886 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.pt-BR.vtt 886 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.es.vtt 886 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.pt-BR.vtt 886 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.en.vtt 886 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences--wbCbKqqaZY.zh-CN.vtt 886 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.zh-CN.vtt 886 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.es-ES.vtt 886 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.ar.vtt 886 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/01. Effect Size-z98xODInLCQ.zh-CN.vtt 885 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.es-ES.vtt 885 B
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.ar.vtt 885 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.en.vtt 884 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.en.vtt 884 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9N6i3RZun5A.zh-CN.vtt 884 B
Part 11-Module 01-Lesson 03_SVM/24. Overfitting-plx_F2BkwNQ.zh-CN.vtt 884 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.pt-BR.vtt 884 B
Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.en.vtt 884 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.es.vtt 883 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.es.vtt 883 B
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.pt-BR.vtt 883 B
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.pt-BR.vtt 883 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.en.vtt 883 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/01. Instructors Introduction-lIvm8urf4GE.zh-CN.vtt 883 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.en.vtt 883 B
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.ar.vtt 882 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.ar.vtt 882 B
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-FOwEL4S-SVo.zh-CN.vtt 881 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.pt-BR.vtt 880 B
Part 11-Module 01-Lesson 04_Decision Trees/35. Decision Tree Mini-Project Video-eFjeXiC0KHA.zh-CN.vtt 880 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.pt-BR.vtt 880 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/01. Lesson Introduction-nQBbywNKTVc.zh-CN.vtt 880 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.es-ES.vtt 880 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.en.vtt 879 B
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.en.vtt 879 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.pt-BR.vtt 879 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.en.vtt 879 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-5Uon6hUTl8Y.zh-CN.vtt 879 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.pt-BR.vtt 879 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.en.vtt 879 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.en.vtt 879 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.pt-BR.vtt 878 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.en.vtt 878 B
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.zh-CN.vtt 878 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.en.vtt 877 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.en.vtt 877 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-pZu3Gr5cAUU.zh-CN.vtt 877 B
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.ar.vtt 876 B
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.en.vtt 876 B
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.ja.vtt 876 B
Part 09-Module 01-Lesson 07_Explore Many Variables/10. Cut a Variable-PHJiH5WCBwg.zh-CN.vtt 876 B
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.pt-BR.vtt 876 B
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/17. Conclusion-D_ioSXAre1A.zh-CN.vtt 876 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-Klv_8052hoA.zh-CN.vtt 875 B
Part 13-Module 01-Lesson 08_Animation and Interaction/38. World Cup Participation Animation-2GN_nwKc_ZA.zh-CN.vtt 875 B
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.en.vtt 875 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/02. Download Tableau Public-2bXsg6SKHG8.en.vtt 875 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.pt-BR.vtt 874 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.en.vtt 874 B
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.ja.vtt 874 B
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.ja.vtt 874 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.en.vtt 874 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.ja.vtt 874 B
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.ar.vtt 874 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.en.vtt 874 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NkyYCLoJVyE.zh-CN.vtt 873 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.en.vtt 873 B
Part 04-Module 02-Lesson 01_Data Analysis Process/15. Getting Data from First Week -adqc5fF5B8Y.zh-CN.vtt 873 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.pt-BR.vtt 873 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.pt-BR.vtt 873 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/09. The Data Science Process-Kxp2TNV3n5k.zh-CN.vtt 873 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.pt-BR.vtt 873 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.en.vtt 872 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.en.vtt 872 B
Part 06-Module 01-Lesson 01_Working with MongoDB/11. Multiple Field Queries-tsAh4HonzIw.zh-CN.vtt 872 B
Part 06-Module 01-Lesson 01_Working with MongoDB/16. Operators-PlJ_dfdEbR0.zh-CN.vtt 872 B
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.pt-BR.vtt 872 B
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.ar.vtt 872 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.ja.vtt 872 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.en.vtt 871 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.en.vtt 871 B
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.ja.vtt 871 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.en.vtt 871 B
Part 03-Module 01-Lesson 11_L4 Variability/13. Match Boxplots-xg4WOp3v-CM.zh-CN.vtt 870 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.pt-BR.vtt 870 B
Part 11-Module 01-Lesson 06_Datasets and Questions/11. Enron Dataset Mini-Project Video-0zGp5er3fy4.zh-CN.vtt 870 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-tEU11PXloLU.zh-CN.vtt 870 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.es-ES.vtt 870 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.pt-BR.vtt 869 B
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.pt-BR.vtt 869 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.ar.vtt 869 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 3-oVGmi4zBOT8.zh-CN.vtt 869 B
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.ar.vtt 868 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.en.vtt 868 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en-GB.vtt 868 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.pt-BR.vtt 867 B
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.pt-BR.vtt 867 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.pt-BR.vtt 867 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.pt-BR.vtt 867 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.es.vtt 866 B
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.pt-BR.vtt 866 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.pt-BR.vtt 866 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.it.vtt 866 B
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.en.vtt 865 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.en.vtt 865 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.ar.vtt 865 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/25. Changing Bin Size-fI_SYnWB1XA.zh-CN.vtt 864 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-q5JgPXsHSrA.zh-CN.vtt 864 B
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.ar.vtt 864 B
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.ar.vtt 864 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.pt-BR.vtt 864 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.pt-BR.vtt 863 B
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.pt-BR.vtt 863 B
Part 09-Module 01-Lesson 07_Explore Many Variables/05. Thinking in Ratios-r4ZOwz3_oXs.zh-CN.vtt 863 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.ar.vtt 863 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.en.vtt 862 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.en.vtt 862 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.es.vtt 862 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.en.vtt 862 B
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.pt-BR.vtt 862 B
Part 11-Module 01-Lesson 12_Feature Selection/07. Getting Rid of Features-JZx1Pyzuo_s.zh-CN.vtt 862 B
Part 11-Module 01-Lesson 12_Feature Selection/12. Bias, Variance Number of Features Pt 2-1lNAvDubBfI.zh-CN.vtt 862 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/07. Traveling Salesman Problem-9ruR5Ux63QU.zh-CN.vtt 862 B
Part 21-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.zh-CN.vtt 862 B
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.pt-BR.vtt 861 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.pt-BR.vtt 861 B
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.pt-BR.vtt 861 B
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.pt-BR.vtt 861 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.ar.vtt 861 B
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.en.vtt 861 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.ar.vtt 861 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.es.vtt 860 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.es.vtt 860 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.en.vtt 860 B
Part 03-Module 01-Lesson 20_L8 Estimation/10. 95 CI with Exact Z-Scores-Ipj62kdE3Lo.zh-CN.vtt 860 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/02. Subway Data-mIn7nMR092Q.zh-CN.vtt 860 B
Part 09-Module 01-Lesson 05_Explore Two Variables/05. Overplotting-qX2W99WrP0k.zh-CN.vtt 860 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/02. Subway Data-mIn7nMR092Q.zh-CN.vtt 860 B
Part 11-Module 01-Lesson 12_Feature Selection/19. Lasso Coefficients with sklearn Quiz-nu2OKJwDvvE.zh-CN.vtt 859 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-qnfVoUChRlQ.zh-CN.vtt 858 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.en.vtt 858 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.zh-CN.vtt 857 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/22. Golden Arches Theory-C9NFjtqf-xU.zh-CN.vtt 857 B
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.en.vtt 857 B
Part 09-Module 01-Lesson 03_Explore One Variable/13. Exploring with Bin Width-TYN_LGAV3m8.zh-CN.vtt 857 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.pt-BR.vtt 857 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.en.vtt 857 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.en.vtt 856 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.en.vtt 856 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.pt-BR.vtt 856 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.pt-BR.vtt 856 B
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.pt-BR.vtt 856 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.en.vtt 856 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.en.vtt 855 B
Part 06-Module 01-Lesson 03_Analyzing Data/01. Introduction to Lesson 5-l2Nab0LY_cI.zh-CN.vtt 855 B
Part 09-Module 01-Lesson 07_Explore Many Variables/15. Bias Variance Trade off Revisited-GGCzMmOpQqQ.zh-CN.vtt 855 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.en.vtt 855 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.pt-BR.vtt 855 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.es.vtt 854 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.ar.vtt 854 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/28. Conclusion-xYqxZQmXCdI.zh-CN.vtt 854 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.hr.vtt 854 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.en.vtt 853 B
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-XtDLvgt7LQk.zh-CN.vtt 853 B
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.en.vtt 853 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.ja.vtt 853 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.pt-BR.vtt 853 B
Part 13-Module 01-Lesson 08_Animation and Interaction/01. Animation and Interaction-4aBXHspd7WI.zh-CN.vtt 853 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/14. Performance Tuning Motivation-aY4_uYWEuoE.zh-CN.vtt 852 B
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.ja.vtt 851 B
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.ar.vtt 851 B
Part 11-Module 01-Lesson 07_Regressions/23. Errors and Fit Quality-PRQDaHphZhw.zh-CN.vtt 850 B
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.pt-BR.vtt 850 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.ar.vtt 850 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.es-ES.vtt 850 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.ar.vtt 850 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/26. Interpret Histogram-Xo3Le7VTZZM.zh-CN.vtt 849 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.pt-BR.vtt 849 B
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.en.vtt 849 B
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.ar.vtt 849 B
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.pt-BR.vtt 849 B
Part 12-Module 02-Lesson 07_Case Studies in Algorithms/01. Case Study Introduction-r8uEDyBylHY.zh-CN.vtt 849 B
Part 13-Module 01-Lesson 04_Design Principles/26. Practical Rules for Using Color-aseCJf5mrdo.zh-CN.vtt 849 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.ar.vtt 849 B
Part 18-Module 04-Lesson 01_Cleaning Data/18. You Can Iterate -CDRmFJHywp8.en.vtt 849 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/01. 26 Spread Part 1-zb76Z_viYLY.zh-CN.vtt 848 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.pt-BR.vtt 848 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.en.vtt 847 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.ja.vtt 847 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-wIXO77zyVxs.zh-CN.vtt 847 B
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.en.vtt 847 B
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.pt-BR.vtt 847 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.ar.vtt 847 B
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.en.vtt 846 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.ar.vtt 846 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.ar.vtt 846 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-aBBmlnd7okQ.ja.vtt 846 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-gl4ogBY9AOI.zh-CN.vtt 845 B
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.pt-BR.vtt 845 B
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.ja.vtt 845 B
Part 11-Module 01-Lesson 04_Decision Trees/10. Decision Tree Parameters-Is5T4alCCGQ.zh-CN.vtt 845 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ar.vtt 845 B
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.es-ES.vtt 845 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.en.vtt 844 B
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.pt-BR.vtt 844 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.pt-BR.vtt 844 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-si8AcC5pTfM.zh-CN.vtt 844 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.ar.vtt 844 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-si8AcC5pTfM.zh-CN.vtt 844 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.pt-BR.vtt 843 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.pt-BR.vtt 843 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.en.vtt 843 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.en.vtt 842 B
Part 11-Module 01-Lesson 03_SVM/04. What Makes A Good Separating Line-yH2wQQt-Rjo.zh-CN.vtt 842 B
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.ja.vtt 842 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-tUeaXXT2oDI.zh-CN.vtt 842 B
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.ar.vtt 842 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.ar.vtt 842 B
Part 13-Module 01-Lesson 05_Dimple.js/33. Advantages with CSS-lCTey7ryZ1A.zh-CN.vtt 842 B
Part 13-Module 01-Lesson 08_Animation and Interaction/47. Start Creating-Nr1w-Hxjld4.zh-CN.vtt 842 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.en.vtt 841 B
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-UAHkVUloKbg.zh-CN.vtt 841 B
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.ar.vtt 841 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/27. Making Decisions about Uncertain Data-GM8MV0FvCUo.zh-CN.vtt 841 B
Part 17-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-GO6kbL3QRBE.ja.vtt 841 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.pt-BR.vtt 840 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.pt-BR.vtt 840 B
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-7rLkGwsbMUY.zh-CN.vtt 840 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.en.vtt 840 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.pt-BR.vtt 840 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.en.vtt 839 B
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.zh-CN.vtt 839 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.pt-BR.vtt 839 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.en.vtt 839 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.zh-CN.vtt 838 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/08. BBC Measurement-t78PB0L8eDU.zh-CN.vtt 838 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.en.vtt 838 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-83VGOXwmjUw.zh-CN.vtt 838 B
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.ar.vtt 838 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ar.vtt 838 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.pt-BR.vtt 837 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.en.vtt 837 B
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.pt-BR.vtt 837 B
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.en.vtt 837 B
Part 11-Module 01-Lesson 03_SVM/26. SVM Mini-Project Video-mENzEtsiOmI.zh-CN.vtt 837 B
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.en.vtt 837 B
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.ar.vtt 837 B
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.es-ES.vtt 837 B
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.it.vtt 837 B
Part 03-Module 01-Lesson 11_L4 Variability/30. Standard Deviation-0seYYIPBXxI.zh-CN.vtt 836 B
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.ar.vtt 836 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.en.vtt 836 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.en.vtt 836 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.es.vtt 835 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.es.vtt 835 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.ko.vtt 835 B
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.ar.vtt 835 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.ja.vtt 835 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.es.vtt 834 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.es.vtt 834 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.pt-BR.vtt 834 B
Part 09-Module 01-Lesson 05_Explore Two Variables/24. Noise in Conditional Means-GKXB5Qjlxo0.zh-CN.vtt 834 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.ja.vtt 834 B
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.pt-BR.vtt 834 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.en.vtt 833 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.es.vtt 832 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.en.vtt 832 B
Part 05-Module 02-Lesson 03_Elements of SQL/16. Wrap Up-BGt2DQer6I4.zh-CN.vtt 832 B
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.es-MX.vtt 832 B
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.pt-BR.vtt 832 B
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.pt-BR.vtt 832 B
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.it.vtt 832 B
Part 09-Module 01-Lesson 05_Explore Two Variables/20. Making Sense of Data-z2rZndd-cdc.zh-CN.vtt 831 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.es.vtt 830 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.pt-BR.vtt 830 B
Part 09-Module 01-Lesson 03_Explore One Variable/08. Faceting-x4V3IyECIN4.zh-CN.vtt 830 B
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.ja.vtt 830 B
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.pt-BR.vtt 830 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.ar.vtt 830 B
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.pt-BR.vtt 830 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/05. Assessing Risk-WjRAjbeG0RE.zh-CN.vtt 830 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/21. Clean Code 1 Solution -Noykh9Zt6aI.zh-CN.vtt 830 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean--IGW7WH6CIA.zh-CN.vtt 829 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.en.vtt 829 B
Part 09-Module 01-Lesson 05_Explore Two Variables/06. coord_trans()-sQe7vTeO0yU.zh-CN.vtt 829 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.pt-BR.vtt 829 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.ar.vtt 829 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.pt-BR.vtt 828 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.en.vtt 828 B
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.en.vtt 828 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.pt-BR.vtt 828 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.en.vtt 828 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.pt-BR.vtt 828 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.en.vtt 828 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-9LrlrexpW_o.zh-CN.vtt 828 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.ja.vtt 828 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.ar.vtt 828 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-7tlVeUW2t7Q.zh-CN.vtt 827 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-BgBEqvjLNig.zh-CN.vtt 827 B
Part 09-Module 01-Lesson 03_Explore One Variable/14. Adjusting the Bin Width-VyYQPDw7w3Y.ja.vtt 827 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.en.vtt 827 B
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.pt-BR.vtt 826 B
Part 13-Module 01-Lesson 05_Dimple.js/28. Changing the Chart Type-wsjvZQaKIgA.zh-CN.vtt 826 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.en.vtt 826 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.en.vtt 826 B
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.zh-CN.vtt 825 B
Part 05-Module 02-Lesson 05_Deeper into SQL/01. Intro to Creating Tables-mIIL-p2gaK4.zh-CN.vtt 825 B
Part 05-Module 02-Lesson 05_Deeper into SQL/18. VIEWs-omL8MVZjLts.zh-CN.vtt 825 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.en-US.vtt 825 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/01. Introduction to Advanced SQL-i0VaVPIKUks.pt-BR.vtt 825 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.pt-BR.vtt 824 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.en.vtt 824 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.ar.vtt 824 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-4Ywln5AT6Hc.zh-CN.vtt 824 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/14. Confidence Intervals-fDkfHKODOcQ.zh-CN.vtt 824 B
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.en.vtt 824 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.es-ES.vtt 823 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.pt-BR.vtt 822 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.pt-BR.vtt 822 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.pt-BR.vtt 822 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.pt-BR.vtt 822 B
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-gUXB5GofFKM.zh-CN.vtt 822 B
Part 05-Module 01-Lesson 05_Data Quality/06. Difficulty of Quality Metrics-uqCSn9Q9ARk.zh-CN.vtt 822 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.en-US.vtt 822 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.ar.vtt 822 B
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.pt-BR.vtt 821 B
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.en.vtt 821 B
Part 13-Module 01-Lesson 07_Narrative Structures/54. Use Variables Wisely-j8o2WUo3-Xg.zh-CN.vtt 821 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.en.vtt 821 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.pt-BR.vtt 820 B
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.ja.vtt 820 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.en.vtt 820 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.ar.vtt 820 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.pt-BR.vtt 819 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/30. Wrap Up - Measures of Center-bsybN1HIH4s.zh-CN.vtt 819 B
Part 05-Module 02-Lesson 03_Elements of SQL/13. Find the Fish Eaters-AnksTk1zI3Y.pt-BR.vtt 819 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.en.vtt 819 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.ar.vtt 819 B
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ar.vtt 819 B
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.ja.vtt 819 B
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.ja.vtt 818 B
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.en-US.vtt 818 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-K4gGK4ScT7M.zh-CN.vtt 818 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/26. Evaluation Mini-Project Video-s13K9G1VaWM.zh-CN.vtt 818 B
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.pt-BR.vtt 818 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.en.vtt 818 B
Part 09-Module 01-Lesson 05_Explore Two Variables/13. Correlation on Subsets-BbBaLbDoPBY.zh-CN.vtt 817 B
Part 11-Module 01-Lesson 04_Decision Trees/01. Welcome To Decision Trees-5eAHVk1-Hz0.zh-CN.vtt 817 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.en.vtt 817 B
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.pt-BR.vtt 817 B
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.en.vtt 817 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.zh-CN.vtt 817 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.es-ES.vtt 817 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-oCQnqFE4uxQ.zh-CN.vtt 816 B
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.en.vtt 816 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.ja.vtt 816 B
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.ar.vtt 816 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.ar.vtt 816 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.ar.vtt 816 B
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.pt-BR.vtt 815 B
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.en.vtt 815 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.pt-BR.vtt 814 B
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-dYbYjtCzQPo.zh-CN.vtt 814 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.pt-BR.vtt 814 B
Part 11-Module 01-Lesson 02_Naive Bayes/37. Congrats on Learning Naive Bayes-nQsYfzO7-00.zh-CN.vtt 814 B
Part 11-Module 01-Lesson 13_PCA/16. Compression While Preserving Information-_TJeoCTDykE.zh-CN.vtt 814 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.pt-BR.vtt 813 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.ja.vtt 813 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.en.vtt 813 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.th.vtt 813 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.ja.vtt 813 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.ar.vtt 812 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.zh-CN.vtt 812 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.pt-BR.vtt 812 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.ja.vtt 812 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-4Fkfu37el_k.zh-CN.vtt 812 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-bgT8sWuV2lc.zh-CN.vtt 812 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-bgT8sWuV2lc.zh-CN.vtt 812 B
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.pt-BR.vtt 811 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-_kmNXcYlrco.en.vtt 811 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/01. Lesson Overview-DkjRzNwjSfo.zh-CN.vtt 811 B
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.en.vtt 810 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.pt-BR.vtt 810 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.en.vtt 810 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-yhzQ_HJcwn8.zh-CN.vtt 810 B
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.ar.vtt 810 B
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.pt-BR.vtt 810 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.en.vtt 809 B
Part 05-Module 02-Lesson 03_Elements of SQL/06. Comparison Operators-0X7voyhbZ8k.zh-CN.vtt 809 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.pt-BR.vtt 809 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.en.vtt 809 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.zh-CN.vtt 808 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/06. BBC Scores-5IhpLHnTZoE.zh-CN.vtt 808 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.es.vtt 808 B
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.en.vtt 808 B
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.zh-CN.vtt 808 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.en.vtt 808 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-pHNtOrr6bgE.zh-CN.vtt 807 B
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.en.vtt 807 B
Part 13-Module 01-Lesson 04_Design Principles/02. Visual Encodings Recap-zyroaZ34ltA.zh-CN.vtt 807 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.ar.vtt 807 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/24. World Peace-0plipvHyAlk.zh-CN.vtt 806 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.en.vtt 806 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/24. World Peace-0plipvHyAlk.zh-CN.vtt 806 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.en.vtt 806 B
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.ja.vtt 806 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.pt-BR.vtt 806 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-Kst3mlrqJnQ.zh-CN.vtt 806 B
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.en.vtt 806 B
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.en.vtt 805 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.ar.vtt 805 B
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.ja.vtt 805 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.en.vtt 804 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.en-GB.vtt 804 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.pt-BR.vtt 803 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.pt-BR.vtt 803 B
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.en.vtt 803 B
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.en.vtt 803 B
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.en.vtt 803 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.pt-BR.vtt 802 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/23. Predictions-hW_1ASU-j8A.zh-CN.vtt 802 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.pt-BR.vtt 802 B
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.pt-BR.vtt 802 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.ar.vtt 802 B
Part 11-Module 01-Lesson 13_PCA/15. From Four Features to Two-xJtmPbEfpFo.zh-CN.vtt 801 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.zh-CN.vtt 799 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/05. BBC Memory Test-R_St8V4O9aQ.zh-CN.vtt 799 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.ar.vtt 799 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-c-pfYggUsdQ.zh-CN.vtt 799 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.en.vtt 799 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ar.vtt 799 B
Part 03-Module 01-Lesson 20_L8 Estimation/28. What Statistics-JKZF4qHztv0.zh-CN.vtt 798 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.en.vtt 798 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.pt-BR.vtt 798 B
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.en.vtt 798 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-Ig82ol_4Lgo.zh-CN.vtt 797 B
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.en.vtt 797 B
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.pt-BR.vtt 797 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-EllzeBecnkU.zh-CN.vtt 797 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.en.vtt 797 B
Part 14-Module 01-Lesson 04_Designing an Experiment/25. Conclusion-YS4bR1vQ3Ls.zh-CN.vtt 797 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.it.vtt 797 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.pt-BR.vtt 797 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.pt-BR.vtt 795 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.es.vtt 794 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.pt-BR.vtt 794 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.pt-BR.vtt 794 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.ar.vtt 794 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.pt-BR.vtt 794 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/02. Alpha Levels-VuEwqXDd1Rs.zh-CN.vtt 793 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.ar.vtt 793 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-FY9_6rOPk6c.zh-CN.vtt 793 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.en.vtt 793 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.en.vtt 792 B
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.en.vtt 792 B
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.ja.vtt 792 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.pt-BR.vtt 792 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.hr.vtt 792 B
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.pt-BR.vtt 791 B
Part 08-Module 03-Lesson 01_Craft Your Cover Letter/06. Write the Conclusion-i3ozyhGPmIg.en.vtt 791 B
Part 11-Module 01-Lesson 16_Tying It All Together/03. End of Content-MFRkl-aXL8I.zh-CN.vtt 791 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.pt-BR.vtt 791 B
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.ar.vtt 791 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/13. Provided Information-FdRVdkASudw.zh-CN.vtt 791 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.en.vtt 790 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.en.vtt 790 B
Part 11-Module 01-Lesson 08_Outliers/03. Outlier Selection-zTI5Ci5WWzM.pt-BR.vtt 790 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.en.vtt 790 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.en.vtt 790 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.ar.vtt 790 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.en.vtt 789 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.en.vtt 789 B
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.en.vtt 789 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.en.vtt 788 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.en.vtt 788 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.en.vtt 788 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.pt-BR.vtt 788 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-diHsJPQHtKc.zh-CN.vtt 787 B
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.en.vtt 787 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/13. Aliases for Multiple Window Functions-RWe03bULYnM.zh-CN.vtt 787 B
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.ar.vtt 787 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-uhrL5fatt3E.zh-CN.vtt 787 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.en.vtt 786 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.es.vtt 786 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.en.vtt 786 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.en.vtt 786 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/01. Where Students Are From-_zx9cahSRNE.zh-CN.vtt 785 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.en.vtt 785 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.pt-BR.vtt 785 B
Part 16-Module 02-Lesson 03_Data Analysis Process - Case Study 2/01. Lesson Overview-2X8GJyZUlDo.zh-CN.vtt 785 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.zh-CN.vtt 785 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.pt-BR.vtt 785 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.en.vtt 784 B
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.ar.vtt 784 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/12. What Can You Create In Tableau-gNqIvf5iJA8.zh-CN.vtt 784 B
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.en.vtt 783 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.en.vtt 783 B
Part 09-Module 01-Lesson 07_Explore Many Variables/20. Prices Over Time-aj_QpA9GygI.zh-CN.vtt 783 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.ja.vtt 783 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.ar.vtt 783 B
Part 11-Module 01-Lesson 08_Outliers/01. Outliers in Regression-_IetITlJpIs.zh-CN.vtt 783 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.pt-BR.vtt 783 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.ar.vtt 783 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/07. Google Account-7C3vCAVaPXo.zh-CN.vtt 782 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/07. Google Account-7C3vCAVaPXo.zh-CN.vtt 782 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.en.vtt 782 B
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.pt-BR.vtt 781 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.pt-BR.vtt 781 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.en.vtt 781 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.zh-CN.vtt 781 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.pt-BR.vtt 781 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.en.vtt 781 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.en.vtt 780 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.en.vtt 780 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-4qJwfAWG_wQ.zh-CN.vtt 780 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.pt-BR.vtt 780 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.zh-CN.vtt 780 B
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.pt-BR.vtt 780 B
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-sl51Cpwy5RA.zh-CN.vtt 779 B
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.en.vtt 779 B
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.pt-BR.vtt 779 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-dGS0SKu1ox0.zh-CN.vtt 779 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.th.vtt 779 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/15. Roll 1 Die-NHnIYEKcnUc.zh-CN.vtt 778 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.en.vtt 778 B
Part 09-Module 01-Lesson 07_Explore Many Variables/14. Friendships Initiated-tNKpdmXj6gg.zh-CN.vtt 778 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-osn2fVnCVgQ.zh-CN.vtt 778 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-lfZg7j5W7u8.zh-CN.vtt 778 B
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.en.vtt 778 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.ar.vtt 778 B
Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.en.vtt 777 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.ar.vtt 777 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.th.vtt 777 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.es-ES.vtt 777 B
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.en.vtt 776 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.pt-BR.vtt 776 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.en.vtt 776 B
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.pt-BR.vtt 775 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.en.vtt 775 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/09. Data Types Summary-T-KrQoAJUpI.zh-CN.vtt 775 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.es-ES.vtt 775 B
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.ar.vtt 774 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.ar.vtt 774 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.ar.vtt 774 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.pt-BR.vtt 774 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-QXFudvtcjv0.zh-CN.vtt 773 B
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.pt-BR.vtt 773 B
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.pt-BR.vtt 773 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.en.vtt 773 B
Part 11-Module 01-Lesson 02_Naive Bayes/06. Classification By Eye-xeMDpSRTLWc.zh-CN.vtt 773 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.pt-BR.vtt 773 B
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.ar.vtt 773 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/31. Lesson Conclusion-quP9Njc2aMg.zh-CN.vtt 773 B
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.pt-BR.vtt 772 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.en.vtt 772 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.th.vtt 772 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en.vtt 772 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.es.vtt 771 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.pt-BR.vtt 771 B
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.ar.vtt 771 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t-tBk_gBWan8k.zh-CN.vtt 770 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.ar.vtt 770 B
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.en.vtt 770 B
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.en.vtt 770 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete--uRSI_oybJQ.pt-BR.vtt 770 B
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.en.vtt 770 B
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.en-US.vtt 770 B
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.pt-BR.vtt 770 B
Part 11-Module 01-Lesson 07_Regressions/24. Minimizing Sum of Squared Errors-E1XzT619Eug.zh-CN.vtt 769 B
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.ar.vtt 769 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.pt-BR.vtt 769 B
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.pt-BR.vtt 769 B
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.ar.vtt 768 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.en.vtt 768 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.th.vtt 768 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.en.vtt 767 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.en.vtt 767 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-KAOIExZuV_M.zh-CN.vtt 767 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.en.vtt 767 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-K2OncV6Bzo8.zh-CN.vtt 767 B
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.en.vtt 767 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.it.vtt 767 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.zh-CN.vtt 766 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/03. Measure Memory-TSm4D-YHvzM.zh-CN.vtt 766 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.en.vtt 766 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.en.vtt 766 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.pt-BR.vtt 766 B
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.pt-BR.vtt 765 B
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.ja.vtt 765 B
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.pt-BR.vtt 765 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ar.vtt 765 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-PT.vtt 765 B
Part 11-Module 01-Lesson 07_Regressions/25. Algorithms for Minimizing Squared Errors-Dw_9Dp6wcJ8.zh-CN.vtt 764 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.it.vtt 764 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.en.vtt 763 B
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-i4lFgFq8Kpo.zh-CN.vtt 763 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.pt-BR.vtt 763 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.ja.vtt 763 B
Part 11-Module 01-Lesson 07_Regressions/08. Continuous Feature Quiz-TIs9j-QITxw.zh-CN.vtt 763 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.zh-CN.vtt 763 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.en.vtt 763 B
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.en.vtt 763 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-dGffszQYzqc.ja.vtt 762 B
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.en-US.vtt 761 B
Part 11-Module 01-Lesson 07_Regressions/11. Slope and Intercept-Ksn1g5fCe1I.zh-CN.vtt 761 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.ar.vtt 761 B
Part 16-Module 03-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.zh-CN.vtt 761 B
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.pt-BR.vtt 761 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.pt-BR.vtt 760 B
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.pt-BR.vtt 760 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.ja.vtt 760 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.en.vtt 759 B
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.en.vtt 759 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.en-US.vtt 759 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.zh-CN.vtt 759 B
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.pt-BR.vtt 758 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.pt-BR.vtt 758 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.ja.vtt 758 B
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.pt-BR.vtt 758 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.en.vtt 757 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.en.vtt 757 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.en.vtt 757 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.es-ES.vtt 757 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.en.vtt 756 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.pt-BR.vtt 756 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.ar.vtt 756 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.en.vtt 756 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.en.vtt 756 B
Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.en.vtt 756 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.en.vtt 754 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.pt-BR.vtt 754 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-VERLCqDewrM.zh-CN.vtt 754 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-fpPPozvkpWM.zh-CN.vtt 754 B
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.en.vtt 754 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-RNgSdHPE4aA.zh-CN.vtt 753 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.zh-CN.vtt 753 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.pt-BR.vtt 753 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.pt-BR.vtt 753 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.pt-BR.vtt 753 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.es.vtt 752 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.en.vtt 752 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-gbkORDbJM50.zh-CN.vtt 752 B
Part 17-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-cDub-OOrIRE.zh-CN.vtt 752 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.en.vtt 752 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ar.vtt 752 B
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.ar.vtt 751 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/36. Hypothesis Testing-GyLWb1FBJsA.zh-CN.vtt 751 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.en.vtt 751 B
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.ar.vtt 751 B
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.en.vtt 751 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.zh-CN.vtt 751 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.es.vtt 750 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.pt-BR.vtt 750 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.en.vtt 750 B
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-llyWJTM8V5o.zh-CN.vtt 750 B
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.pt-BR.vtt 750 B
Part 09-Module 01-Lesson 07_Explore Many Variables/13. Friending Rate-J0IqMgkl1Ws.zh-CN.vtt 750 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.zh-CN.vtt 750 B
Part 17-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.zh-CN.vtt 750 B
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.en.vtt 749 B
Part 03-Module 01-Lesson 20_L8 Estimation/09. Sampling Distribution-XUA8rsit0J4.zh-CN.vtt 749 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature--_jNi_5zEEQ.zh-CN.vtt 749 B
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.pt-BR.vtt 749 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.en.vtt 748 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-_HWtxJRaawA.zh-CN.vtt 748 B
Part 11-Module 01-Lesson 03_SVM/07. SVM Response to Outliers-TEAGqUkQVdM.zh-CN.vtt 748 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.hr.vtt 748 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.es-ES.vtt 748 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.ja.vtt 748 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-pUaHzMlfxrk.zh-CN.vtt 747 B
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.pt-BR.vtt 747 B
Part 09-Module 01-Lesson 01_What is EDA/06. The Growth of Televisions-r5qca6q4Fn4.zh-CN.vtt 747 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.zh-CN.vtt 747 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.en.vtt 747 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt 747 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt 747 B
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.en.vtt 747 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt 747 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt 747 B
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.en.vtt 746 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.en.vtt 746 B
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.pt-BR.vtt 746 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.es-ES.vtt 746 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.es-ES.vtt 746 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.pt-BR.vtt 746 B
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.pt-BR.vtt 746 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.en.vtt 745 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.ar.vtt 745 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.zh-CN.vtt 745 B
Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.pt-BR.vtt 745 B
Part 21-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.zh-CN.vtt 745 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.en.vtt 744 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/23. Wrap-Up-DZa6UOGet_g.zh-CN.vtt 744 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-R6oIvdBtsZw.zh-CN.vtt 744 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.en.vtt 743 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.pt-BR.vtt 743 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.zh-CN.vtt 743 B
Part 09-Module 01-Lesson 07_Explore Many Variables/11. Plotting It All Together-Y4rUkaYQQKI.zh-CN.vtt 743 B
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.pt-BR.vtt 743 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.pt-BR.vtt 743 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.ar.vtt 743 B
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.pt-BR.vtt 742 B
Part 05-Module 02-Lesson 01_Data and Tables/03. Looking at Tables-08GsrEIOP9Q.zh-CN.vtt 742 B
Part 09-Module 01-Lesson 05_Explore Two Variables/03. Scatterplots-ZcavaOLXPSs.zh-CN.vtt 742 B
Part 12-Module 02-Lesson 05_Trees/01. Trees-PXie7f22v2Q.zh-CN.vtt 742 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.pt-BR.vtt 742 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.pt-BR.vtt 742 B
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.en.vtt 742 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.it.vtt 742 B
Part 17-Module 01-Lesson 11_Confidence Intervals/16. Confidence Intervals And Hypothesis Tests-T2d9AUnWl-I.zh-CN.vtt 742 B
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.en.vtt 742 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.pt-BR.vtt 741 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.zh-CN.vtt 741 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.pt-BR.vtt 741 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.es-ES.vtt 741 B
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.pt-BR.vtt 740 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-QheTapjHFdU.zh-CN.vtt 740 B
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.en.vtt 740 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-Ld7EaNyua4c.zh-CN.vtt 740 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.en.vtt 739 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.pt-BR.vtt 739 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.ar.vtt 739 B
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.pt-BR.vtt 739 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.pt-BR.vtt 739 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/14. Internal Training-E55ujT-kf5E.zh-CN.vtt 739 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ar.vtt 738 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.en.vtt 738 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.pt-BR.vtt 737 B
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.ar.vtt 737 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.pt-BR.vtt 737 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.pt-BR.vtt 737 B
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.en.vtt 736 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-yLeLxDyXCSY.zh-CN.vtt 736 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.pt-BR.vtt 736 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.en.vtt 736 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/01. Introduction-2Y279421n3A.zh-CN.vtt 736 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.pt-BR.vtt 736 B
Part 17-Module 01-Lesson 15_Multiple Linear Regression/26. Recap-VM6GGNC2q8I.zh-CN.vtt 736 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.en.vtt 736 B
Part 06-Module 01-Lesson 03_Analyzing Data/20. Congrats-quszTmIRG8M.zh-CN.vtt 735 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.ja.vtt 735 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.pt-BR.vtt 735 B
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.pt-BR.vtt 735 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.en.vtt 734 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.en.vtt 734 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.pt-BR.vtt 734 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.en.vtt 734 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.pt-BR.vtt 733 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.pt-BR.vtt 733 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.en.vtt 733 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.zh-CN.vtt 733 B
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.pt-BR.vtt 733 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.en.vtt 733 B
Part 05-Module 02-Lesson 01_Data and Tables/11. Favorite Animals-O7kWdC8ffEw.zh-CN.vtt 732 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.en.vtt 732 B
Part 11-Module 01-Lesson 14_Validation/14. On to the Validation Mini-Project-JEK7-ocWu0M.zh-CN.vtt 732 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.en.vtt 732 B
Part 03-Module 01-Lesson 11_L4 Variability/03. What's the Difference-CJ_C0FZBCPY.zh-CN.vtt 731 B
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.es-ES.vtt 731 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.pt-BR.vtt 731 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.ar.vtt 731 B
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.ar.vtt 731 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.pt-BR.vtt 730 B
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.en.vtt 730 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.en.vtt 730 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.ja.vtt 730 B
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.pt-BR.vtt 729 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.en.vtt 729 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.th.vtt 729 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.es-ES.vtt 729 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.es.vtt 728 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.en.vtt 728 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.en.vtt 728 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.pt-BR.vtt 728 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.en.vtt 728 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.pt-BR.vtt 728 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.es-ES.vtt 728 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.en.vtt 728 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/10. Intro to Screen Scraping-RJyVIgUUemE.en.vtt 727 B
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.ja.vtt 727 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.ar.vtt 727 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.ar.vtt 726 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.ar.vtt 726 B
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.pt-BR.vtt 724 B
Part 21-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.zh-CN.vtt 724 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-XCf2FDdHDGs.zh-CN.vtt 723 B
Part 07-Module 01-Lesson 01_GitHub Review/16. Outro-dps7Ti6Lado.zh-CN.vtt 723 B
Part 09-Module 01-Lesson 07_Explore Many Variables/25. Scatterplot Matrices-ov--BE6XTZU.zh-CN.vtt 723 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.th.vtt 723 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-oIFRsiD2mQE.pt-BR.vtt 722 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.en.vtt 722 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/10. Decision Tree Confusion Matrix-cUlEryXX9BM.zh-CN.vtt 722 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.ar.vtt 722 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/10. More o' Mode!-wBduq7St2Ak.zh-CN.vtt 721 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.ar.vtt 721 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/15. Standardizing Each Column Again-7NofF-s1UGY.zh-CN.vtt 720 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-WxAWorS2SLg.zh-CN.vtt 720 B
Part 13-Module 01-Lesson 04_Design Principles/34. Determining a Graphic's Effectiveness-BZERcWwQ-PM.zh-CN.vtt 720 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/15. Standardizing Each Column Again-7NofF-s1UGY.zh-CN.vtt 720 B
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.pt-BR.vtt 719 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.ar.vtt 719 B
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.en.vtt 719 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.en.vtt 718 B
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.ar.vtt 718 B
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.pt-BR.vtt 717 B
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.pt-BR.vtt 717 B
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.en.vtt 717 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.pt-BR.vtt 717 B
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.en-US.vtt 717 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.en.vtt 717 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ar.vtt 717 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.ja.vtt 717 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.th.vtt 717 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.pt-BR.vtt 716 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.pt-BR.vtt 716 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.pt-BR.vtt 716 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.ja.vtt 716 B
Part 16-Module 03-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.zh-CN.vtt 715 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.en.vtt 715 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.en.vtt 715 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pl.vtt 715 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.zh-CN.vtt 714 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9-dCjOMkrRw.zh-CN.vtt 714 B
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.pt-BR.vtt 714 B
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.en.vtt 714 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.en.vtt 714 B
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.en.vtt 713 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.ar.vtt 713 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.ar.vtt 713 B
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.zh-CN.vtt 713 B
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.pt-BR.vtt 712 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/25. NEW Create a Radius Scale-SUj-uKarNt0.zh-CN.vtt 712 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.pt-BR.vtt 712 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.pt-BR.vtt 712 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-P46v39eNSqM.zh-CN.vtt 712 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.it.vtt 712 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.es.vtt 711 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.pt-BR.vtt 711 B
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.pt-BR.vtt 711 B
Part 11-Module 01-Lesson 10_Feature Scaling/13. Feature Scaling Mini-Project Video-e6zbTFctnJU.zh-CN.vtt 711 B
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.ar.vtt 711 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.en.vtt 711 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.es.vtt 710 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ja.vtt 710 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.es.vtt 709 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.es.vtt 709 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.pt-BR.vtt 709 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.en.vtt 709 B
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.en.vtt 709 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.pt-BR.vtt 709 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.es.vtt 708 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.zh-CN.vtt 708 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.es.vtt 708 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/15. Control for Time of Day-ZFPsrfUZ0ZU.zh-CN.vtt 708 B
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.ja.vtt 708 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.ja.vtt 708 B
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.ar.vtt 708 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.ja.vtt 708 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.zh-CN.vtt 708 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/11. Acne Medication-Xt2k2PWBwm4.zh-CN.vtt 707 B
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.es-MX.vtt 707 B
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.pt-BR.vtt 707 B
Part 17-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.zh-CN.vtt 707 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ar.vtt 706 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.pt-BR.vtt 705 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.pt-BR.vtt 705 B
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.en.vtt 705 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.pt-BR.vtt 705 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/03. Z-Critical Value 0.05-TyqZdKR8J_w.zh-CN.vtt 704 B
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.pt-BR.vtt 704 B
Part 11-Module 01-Lesson 02_Naive Bayes/35. Why Is Naive Bayes Naive-Bw6sYY84cYg.zh-CN.vtt 704 B
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.ar.vtt 704 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.en.vtt 704 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.zh-CN.vtt 704 B
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.ar.vtt 704 B
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.ar.vtt 703 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-EPrrQaYp7H0.zh-CN.vtt 703 B
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.zh-CN.vtt 703 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.nl.vtt 702 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.en.vtt 702 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.it.vtt 702 B
Part 17-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.pt-BR.vtt 702 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.pt-BR.vtt 701 B
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.ja.vtt 701 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-daVA3PI2E6o.zh-CN.vtt 701 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.pt-BR.vtt 701 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-PRjmvj6Vubs.zh-CN.vtt 701 B
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.pt-BR.vtt 701 B
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.pt-BR.vtt 701 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.zh-CN.vtt 701 B
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.ar.vtt 700 B
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.pt-BR.vtt 700 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.th.vtt 700 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.pt-BR.vtt 700 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.zh-CN.vtt 699 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/33. Control for What-F-PiFb6Jcrk.zh-CN.vtt 699 B
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.en.vtt 699 B
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.en.vtt 699 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.pt-BR.vtt 699 B
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.pt-BR.vtt 698 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ujpjeaxE6GU.zh-CN.vtt 698 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt 698 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.en.vtt 698 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.pt-BR.vtt 698 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt 698 B
Part 11-Module 01-Lesson 04_Decision Trees/14. Minimizing Impurity in Splitting-L6J6BRFgDiI.pt-BR.vtt 697 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.ar.vtt 697 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.en.vtt 697 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.it.vtt 697 B
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.es.vtt 696 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/04. Relative Frequency-NTyY1HlXhiQ.zh-CN.vtt 696 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-htd-vu8q3po.zh-CN.vtt 696 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.pt-BR.vtt 696 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.pt-BR.vtt 696 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.pt-BR.vtt 696 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/01. Introduction-wwzSxJvGwf0.zh-CN.vtt 695 B
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.pt-BR.vtt 695 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.it.vtt 695 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.pt-BR.vtt 695 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.pt-BR.vtt 695 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/01. Introduction-wwzSxJvGwf0.zh-CN.vtt 695 B
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.pt-BR.vtt 694 B
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.zh-CN.vtt 694 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-IC47yHGmgMk.zh-CN.vtt 694 B
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.ar.vtt 694 B
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.pt-BR.vtt 694 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-lK2lDLdE6iA.zh-CN.vtt 693 B
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.en.vtt 693 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.pt-BR.vtt 693 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.pt-BR.vtt 693 B
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.pt-BR.vtt 693 B
Part 18-Module 03-Lesson 01_Assessing Data/20. You Can Iterate-ZU8EnPbR-pk.pt-BR.vtt 693 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.ar.vtt 693 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.pt-BR.vtt 693 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/08. 24. Classical Music-3hSAWKrdO5s.zh-CN.vtt 692 B
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.pt-BR.vtt 692 B
Part 09-Module 01-Lesson 03_Explore One Variable/19. User Ages-BmGqdHagFQk.zh-CN.vtt 692 B
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.en.vtt 692 B
Part 12-Module 02-Lesson 01_Introduction and Efficiency/04. Syntax-08M93RaBSgU.zh-CN.vtt 692 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.pt-BR.vtt 692 B
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.pt-BR.vtt 692 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.pt-BR.vtt 691 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.pt-BR.vtt 691 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.pt-BR.vtt 691 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.pt-BR.vtt 691 B
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.en.vtt 690 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.en.vtt 690 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.pt-BR.vtt 690 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.en.vtt 690 B
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.pt-BR.vtt 690 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.hr.vtt 690 B
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.en.vtt 690 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-90OMETgfDyk.zh-CN.vtt 689 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-90OMETgfDyk.zh-CN.vtt 689 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.pt-BR.vtt 689 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.pt-BR.vtt 689 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.pt-BR.vtt 688 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.pt-BR.vtt 688 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/28. Probability of Obtaining Mean-00SWFc0sFIg.zh-CN.vtt 688 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.en.vtt 688 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/20. Shoes - 95 CI-hN3Js3thgdY.zh-CN.vtt 688 B
Part 11-Module 01-Lesson 12_Feature Selection/20. Using Lasso in sklearn Quiz-xYxD4GD1woo.zh-CN.vtt 688 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.pt-BR.vtt 688 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.en.vtt 688 B
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.pt-BR.vtt 688 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.pt-BR.vtt 688 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.en.vtt 687 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.en.vtt 687 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.pt-BR.vtt 687 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.pt-BR.vtt 687 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.es.vtt 686 B
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.pt-BR.vtt 686 B
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-AocpFl2wt6k.zh-CN.vtt 686 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.pt-BR.vtt 686 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.es-ES.vtt 686 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-8LDZzqrCnS0.zh-CN.vtt 685 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/01. Intro to the PDF-QTVWqk09q1A.zh-CN.vtt 685 B
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.ko.vtt 685 B
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.en.vtt 685 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.ar.vtt 685 B
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.en.vtt 685 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.pt-BR.vtt 684 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.pt-BR.vtt 684 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.en.vtt 684 B
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.pt-BR.vtt 684 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ar.vtt 684 B
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.ar.vtt 684 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ar.vtt 684 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.pt-BR.vtt 684 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/28. Placebo-IJZs7KARtFo.zh-CN.vtt 683 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/28. Placebo-IJZs7KARtFo.zh-CN.vtt 683 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.pt-BR.vtt 683 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/11. Two-Tailed Test-4fWHT1f72B8.zh-CN.vtt 683 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-nCg6F5QQZsI.zh-CN.vtt 683 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/22. A Bigger, Better Data Set-uj6bLK91ZQI.zh-CN.vtt 683 B
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.pt-BR.vtt 683 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.ar.vtt 683 B
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.ar.vtt 683 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-VdVjOC6UP6c.zh-CN.vtt 682 B
Part 03-Module 01-Lesson 11_L4 Variability/07. Chop Off the Tails-NmlhFjNHmXc.zh-CN.vtt 682 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/10. Calculate SDs-x-VMDl-3p7M.zh-CN.vtt 682 B
Part 05-Module 02-Lesson 01_Data and Tables/06. Zoo-YG8zfeRXAvM.en.vtt 682 B
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.en.vtt 682 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.ar.vtt 682 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.en.vtt 682 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.en.vtt 682 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.es-ES.vtt 682 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.en.vtt 682 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.es.vtt 681 B
Part 13-Module 01-Lesson 08_Animation and Interaction/20. Adding Circles to the Map-y_Hp6nNKxdM.zh-CN.vtt 681 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.es-ES.vtt 681 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.en.vtt 680 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.en.vtt 680 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-lS5DfbsWH34.zh-CN.vtt 680 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.en.vtt 680 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.pt-BR.vtt 680 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.pt-BR.vtt 679 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.en.vtt 679 B
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.en.vtt 679 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.en.vtt 679 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.en.vtt 679 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.ar.vtt 679 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.es-ES.vtt 679 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.es-ES.vtt 679 B
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.pt-BR.vtt 678 B
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.pt-BR.vtt 678 B
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.ar.vtt 678 B
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.pt-BR.vtt 678 B
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.en.vtt 678 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.en.vtt 677 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.en.vtt 677 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/01. Which Major-t0yIetl9ZxI.zh-CN.vtt 677 B
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.en.vtt 677 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-c1gvsNx_ypg.zh-CN.vtt 677 B
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.ar.vtt 677 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-9O7cJSP4C8w.zh-CN.vtt 677 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.th.vtt 677 B
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.pt-BR.vtt 677 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.en.vtt 676 B
Part 03-Module 01-Lesson 13_L5 Standardizing/21. Standard Normal Distribution-5B-vrhyedws.zh-CN.vtt 676 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/21. Great Job!-fm66AGJzRI0.zh-CN.vtt 676 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-DrnAR4SqlEE.zh-CN.vtt 676 B
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.pt-BR.vtt 675 B
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.zh-CN.vtt 675 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.en.vtt 675 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.ar.vtt 675 B
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.en.vtt 675 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.zh-CN.vtt 675 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.ar.vtt 675 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.zh-CN.vtt 674 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/26. Benefits of Surveys-yw4LmtAVXGY.zh-CN.vtt 674 B
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.en.vtt 674 B
Part 03-Module 01-Lesson 11_L4 Variability/10. IQR-9dYN_oIly9I.zh-CN.vtt 673 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/06. 2 SDs Below or Above-lGHZ4w8UqIk.zh-CN.vtt 673 B
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.en.vtt 673 B
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.pt-BR.vtt 673 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.ar.vtt 673 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.zh-CN.vtt 673 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.pt-BR.vtt 673 B
Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.ar.vtt 673 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/24. Order Measures of Center 1-Im9nOwm_fS8.zh-CN.vtt 672 B
Part 11-Module 01-Lesson 07_Regressions/01. Continuous Output Quiz-udJvijJvs1M.zh-CN.vtt 672 B
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.pt-BR.vtt 672 B
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.en.vtt 672 B
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.en.vtt 671 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/10. Report CI Results 2-eVTzjsolEwI.zh-CN.vtt 671 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.pt-BR.vtt 671 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-KEdbHg_utV0.zh-CN.vtt 671 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.pt-BR.vtt 671 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.es-ES.vtt 671 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.it.vtt 671 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.es-ES.vtt 671 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ar.vtt 670 B
Part 17-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.zh-CN.vtt 670 B
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.en.vtt 669 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.ar.vtt 669 B
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.ar.vtt 669 B
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.ar.vtt 669 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ja.vtt 669 B
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.en.vtt 668 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.en.vtt 668 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-ePXAzoGVviM.zh-CN.vtt 668 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.pt-BR.vtt 667 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/31. Raining-UNASgS676Hc.zh-CN.vtt 667 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.th.vtt 667 B
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.en.vtt 666 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.en.vtt 666 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.zh-CN.vtt 665 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.zh-CN.vtt 665 B
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.en.vtt 665 B
Part 11-Module 01-Lesson 12_Feature Selection/11. Bias, Variance, and Number of Features-mpYpT6nZVEo.zh-CN.vtt 665 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.ar.vtt 665 B
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.es-ES.vtt 665 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.ar.vtt 665 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.en.vtt 664 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/12. Using the Z-Table-EeT7osOfzJE.zh-CN.vtt 664 B
Part 11-Module 01-Lesson 03_SVM/21. Kernel and Gamma-znlTyocTgSc.zh-CN.vtt 664 B
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.en.vtt 664 B
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-UbnrfnB8vcs.zh-CN.vtt 663 B
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.ar.vtt 663 B
Part 08-Module 01-Lesson 01_Conduct a Job Search/04. Open Yourself Up to Opportunity-1OamTNkk1xM.en.vtt 663 B
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.pt-BR.vtt 663 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ar.vtt 663 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.en.vtt 663 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.es.vtt 662 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-i6zv8vyZBk0.zh-CN.vtt 662 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt 662 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.ar.vtt 662 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.hr.vtt 662 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.ar.vtt 662 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.ar.vtt 662 B
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.en.vtt 661 B
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.pt-BR.vtt 661 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ja.vtt 661 B
Part 18-Module 03-Lesson 01_Assessing Data/13. Date Quality Dimensions 2 -aEGtqoWIJIc.zh-CN.vtt 661 B
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.ar.vtt 660 B
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.en.vtt 660 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.en.vtt 660 B
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.pt-BR.vtt 660 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.pt-BR.vtt 660 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.pt-BR.vtt 660 B
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.ar.vtt 660 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download Solution-SDqdLhgsBNc.zh-CN.vtt 660 B
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.en.vtt 660 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test-zqj1NZbe5os.zh-CN.vtt 659 B
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.en.vtt 658 B
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.en.vtt 658 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.ar.vtt 658 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.en.vtt 658 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.zh-CN.vtt 658 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.en.vtt 658 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.en.vtt 658 B
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.pt-BR.vtt 657 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.th.vtt 657 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.ja.vtt 657 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.pt-BR.vtt 656 B
Part 03-Module 01-Lesson 11_L4 Variability/37. Sample SD-1SL8FGhaKqA.zh-CN.vtt 656 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/21. Model Problems-Och80L_uNjU.zh-CN.vtt 656 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line---Pc1ASVjmM.zh-CN.vtt 656 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.en.vtt 656 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.es-ES.vtt 656 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.it.vtt 656 B
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ar.vtt 656 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-ydpbvqLmLQI.zh-CN.vtt 655 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.en.vtt 655 B
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.ja.vtt 655 B
Part 11-Module 01-Lesson 11_Text Learning/12. Order of Operations in Text Processing-Fi3uuGj8bhs.zh-CN.vtt 655 B
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.pt-BR.vtt 655 B
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.en.vtt 655 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.en.vtt 655 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-icmKCnOXQdI.zh-CN.vtt 654 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.pt-BR.vtt 654 B
Part 13-Module 01-Lesson 07_Narrative Structures/45. Parsing Attendance--5--eKjgU7k.zh-CN.vtt 654 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.th.vtt 654 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ar.vtt 654 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.en.vtt 653 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/15. SD of Karma Points per Post-gIR0M2Jxb0k.zh-CN.vtt 653 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.ja.vtt 653 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.pt-BR.vtt 653 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.en.vtt 653 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.th.vtt 653 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.pt-BR.vtt 652 B
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.ar.vtt 652 B
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.en.vtt 652 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.ar.vtt 652 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.pt-BR.vtt 652 B
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.zh-CN.vtt 652 B
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.ar.vtt 652 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.pt-BR.vtt 651 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.zh-CN.vtt 650 B
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.en.vtt 650 B
Part 13-Module 01-Lesson 08_Animation and Interaction/33. Highlight Countries-wjUenfTcSG0.zh-CN.vtt 650 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.en.vtt 650 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ar.vtt 650 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ar.vtt 650 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.zh-CN.vtt 650 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.en.vtt 649 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.en.vtt 649 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.en.vtt 649 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.en.vtt 649 B
Part 05-Module 02-Lesson 05_Deeper into SQL/10. Self JOINs-dHS0BtLFTSQ.zh-CN.vtt 649 B
Part 09-Module 01-Lesson 03_Explore One Variable/07. Perceived Audience Size-zHnhKtVMhuc.zh-CN.vtt 649 B
Part 11-Module 01-Lesson 12_Feature Selection/05. Beware of Feature Bugs!-UjaFiRdHPZg.zh-CN.vtt 649 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.pt-BR.vtt 648 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.ja.vtt 647 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.pt-BR.vtt 646 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.en.vtt 646 B
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.pt-BR.vtt 646 B
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.ja.vtt 646 B
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.en.vtt 646 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.en.vtt 646 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.en.vtt 646 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.en.vtt 646 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.pt-BR.vtt 645 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.en.vtt 645 B
Part 11-Module 01-Lesson 08_Outliers/02. What Causes Outliers-W74CdB_pl5M.zh-CN.vtt 645 B
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.en.vtt 645 B
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.en.vtt 644 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-0iKPoKeApJI.zh-CN.vtt 644 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-tSZJDW3qp_I.zh-CN.vtt 644 B
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.ja.vtt 644 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.pt-BR.vtt 644 B
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.ar.vtt 644 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.en.vtt 644 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.zh-CN.vtt 644 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/08. Gather Download-a5o3ck1bxEs.zh-CN.vtt 644 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.pt-BR.vtt 644 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-XhVy8ALgO0U.zh-CN.vtt 643 B
Part 11-Module 01-Lesson 03_SVM/01. Welcome to SVM-gnAmmyQ_ZcQ.zh-CN.vtt 643 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.pt-BR.vtt 643 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.zh-CN.vtt 643 B
Part 17-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.zh-CN.vtt 643 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-bD9ULWEsW0M.zh-CN.vtt 642 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-PPcSvB1htPc.zh-CN.vtt 642 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.pt-BR.vtt 642 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.pt-BR.vtt 642 B
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.pt-BR.vtt 641 B
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.en.vtt 641 B
Part 13-Module 01-Lesson 08_Animation and Interaction/36. Animating Each Year-o_qyeIeRb_Y.en.vtt 641 B
Part 18-Module 02-Lesson 01_Gathering Data/07. Flat Files in Python -cUmcLjWgxwM.zh-CN.vtt 641 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.pt-BR.vtt 640 B
Part 03-Module 01-Lesson 20_L8 Estimation/22. Standard Error-w-7MoreKqaU.zh-CN.vtt 640 B
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.pt-BR.vtt 640 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.en.vtt 640 B
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.en.vtt 640 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.hr.vtt 640 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ar.vtt 640 B
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.en.vtt 639 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.pt-BR.vtt 639 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.en.vtt 639 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.en.vtt 638 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.pt-BR.vtt 638 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.zh-CN.vtt 638 B
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.en.vtt 637 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.ja.vtt 637 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.hr.vtt 637 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.pt-BR.vtt 637 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.ar.vtt 636 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.pt-BR.vtt 636 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.en.vtt 636 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.pt-BR.vtt 636 B
Part 05-Module 02-Lesson 01_Data and Tables/17. Summary-1Gp4l-ZTCVk.zh-CN.vtt 635 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.ar.vtt 635 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.en.vtt 635 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.ar.vtt 635 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.en.vtt 635 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.en.vtt 634 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.en.vtt 634 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.en.vtt 634 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.th.vtt 634 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.en.vtt 634 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.pt-BR.vtt 633 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.pt-BR.vtt 633 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.en.vtt 633 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.en.vtt 633 B
Part 09-Module 01-Lesson 05_Explore Two Variables/16. Strong Correlations-QsWzjYigYB4.zh-CN.vtt 633 B
Part 11-Module 01-Lesson 09_Clustering/16. Counterintuitive Clusters 2-xSQTzAeeoEc.zh-CN.vtt 633 B
Part 17-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.zh-CN.vtt 633 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.en.vtt 633 B
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words-kgc_y-oJObM.zh-CN.vtt 632 B
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.ja.vtt 632 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.ja.vtt 632 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.en-US.vtt 632 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.ar.vtt 632 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/19. Exploring Data With Visuals-0i_9t4Wi0Og.zh-CN.vtt 632 B
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.ar.vtt 631 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.ar.vtt 631 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/12. Procedure for Finding Mean-nRurXCTYxG4.zh-CN.vtt 630 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.ar.vtt 630 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-HNo0KSYM2b4.zh-CN.vtt 630 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.pt-BR.vtt 630 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.en.vtt 630 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.ar.vtt 630 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.en.vtt 629 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.en.vtt 629 B
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.ar.vtt 629 B
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.pt-BR.vtt 629 B
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.pt-BR.vtt 629 B
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.en.vtt 629 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.pt-BR.vtt 629 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.zh-CN.vtt 629 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.es-ES.vtt 629 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/09. Report CI Results-pr-2ZaCDzPY.zh-CN.vtt 628 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.pt-BR.vtt 628 B
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.pt-BR.vtt 628 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.ja.vtt 628 B
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.pt-BR.vtt 628 B
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.en.vtt 628 B
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.en.vtt 627 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/20. Top 5-HbS35vDe_x0.zh-CN.vtt 627 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.en.vtt 627 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-L4Jgcf9FNKA.zh-CN.vtt 627 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-UPRiS4xRnow.zh-CN.vtt 627 B
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.zh-CN.vtt 627 B
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.pt-BR.vtt 627 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-AI9kNE00Los.zh-CN.vtt 627 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.ja.vtt 627 B
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.en.vtt 626 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.en.vtt 626 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.pt-BR.vtt 626 B
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.pt-BR.vtt 626 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.zh-CN.vtt 626 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.pt-BR.vtt 626 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.en.vtt 626 B
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.ar.vtt 626 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.ar.vtt 626 B
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-SADDVcUMQXM.zh-CN.vtt 625 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.pt-BR.vtt 625 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.ja.vtt 625 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.it.vtt 625 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-6yT3SlcmTl8.zh-CN.vtt 624 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.ar.vtt 624 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.ar.vtt 624 B
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.zh-CN.vtt 623 B
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.en.vtt 623 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.ja.vtt 623 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ar.vtt 623 B
Part 03-Module 01-Lesson 20_L8 Estimation/16. Z for 98 CI-fFY4isvV-Sk.zh-CN.vtt 622 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.ar.vtt 622 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.ar.vtt 622 B
Part 11-Module 01-Lesson 07_Regressions/06. Phone Number Continuous or Discrete-5dt0N4XN-y4.zh-CN.vtt 622 B
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.en.vtt 622 B
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.ar.vtt 622 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.en.vtt 622 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3-m1LSU9SPZ2k.zh-CN.vtt 622 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.es.vtt 621 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.ja.vtt 621 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.en.vtt 620 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.es.vtt 620 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.en.vtt 620 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.es.vtt 620 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.pt-BR.vtt 620 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.ar.vtt 620 B
Part 09-Module 01-Lesson 07_Explore Many Variables/28. Analyzing Three or More Variables-hcGeA_0nru8.ja.vtt 620 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/21. Conclusion-UFwgr6tLcuI.zh-CN.vtt 620 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/19. Congratulations!-_FPpbuuW-1o.pt-BR.vtt 620 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.pt-BR.vtt 620 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.en.vtt 619 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.en.vtt 619 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.en.vtt 619 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.en.vtt 619 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt 618 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.it.vtt 618 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ja.vtt 618 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt 618 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/12. Congratulations!-sCQ7ZViODaw.zh-CN.vtt 618 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.en-US.vtt 617 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.ar.vtt 617 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ja.vtt 617 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ru.vtt 617 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.en.vtt 617 B
Part 17-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.zh-CN.vtt 617 B
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.en.vtt 617 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en-US.vtt 617 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-tPVKll2xFUw.zh-CN.vtt 616 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Fzich-V7ZO0.zh-CN.vtt 616 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.pt-BR.vtt 616 B
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.pt-BR.vtt 616 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.ar.vtt 616 B
Part 16-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.zh-CN.vtt 616 B
Part 17-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.zh-CN.vtt 616 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.zh-CN.vtt 616 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.ar.vtt 616 B
Part 03-Module 01-Lesson 13_L5 Standardizing/16. Formula for Number of SDs-PXHHbaYnciY.zh-CN.vtt 615 B
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.pt-BR.vtt 615 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ar.vtt 615 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.pt-BR.vtt 614 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.ja.vtt 614 B
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.pt-BR.vtt 613 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.en.vtt 613 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.en.vtt 613 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/06. Inspecting Elements-zAQygY7v2Ds.zh-CN.vtt 613 B
Part 17-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.zh-CN.vtt 613 B
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-E931DQC0hno.zh-CN.vtt 612 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.pt-BR.vtt 612 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.pt-BR.vtt 612 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-a1sLkQtfUKc.zh-CN.vtt 611 B
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.pt-BR.vtt 611 B
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.zh-CN.vtt 611 B
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.en.vtt 611 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.ja.vtt 611 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.es-ES.vtt 611 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.en.vtt 610 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.en.vtt 610 B
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.zh-CN.vtt 610 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.en.vtt 610 B
Part 13-Module 01-Lesson 04_Design Principles/10. Chart Types-OVoEIInUg9A.zh-CN.vtt 610 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en.vtt 610 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/22. Gender and Shoes-FxF9WyIPFbo.zh-CN.vtt 609 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.ar.vtt 609 B
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.en.vtt 609 B
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.ar.vtt 609 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.zh-CN.vtt 609 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.ar.vtt 609 B
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.pt-BR.vtt 608 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.zh-CN.vtt 608 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/14. Influence Memory-tM3xOOtcSL4.zh-CN.vtt 608 B
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.en.vtt 608 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.pt-BR.vtt 608 B
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.ar.vtt 608 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.pt-BR.vtt 608 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-8vi9b_LHHz8.zh-CN.vtt 608 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.es-ES.vtt 608 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ja.vtt 608 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ar.vtt 607 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-Ee2o-0arldg.zh-CN.vtt 606 B
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-jNUbORceQPA.zh-CN.vtt 606 B
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.hi.vtt 606 B
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.pt-BR.vtt 606 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/12. Gather Import Solution-QnTPEAGXJaE.zh-CN.vtt 606 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.en.vtt 605 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.en-US.vtt 605 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/18. Roll 5 Dice-GVoO-G6g3i0.zh-CN.vtt 604 B
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.ar.vtt 604 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.th.vtt 604 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.th.vtt 603 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.es.vtt 602 B
Part 03-Module 01-Lesson 11_L4 Variability/14. Mean Within IQR-o2n0nea_1T0.zh-CN.vtt 602 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/32. Location of Mean on Distribution-k3RUgrtFIl4.zh-CN.vtt 602 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.ar.vtt 602 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.en.vtt 602 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.pt-BR.vtt 602 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.pt-BR.vtt 601 B
Part 03-Module 01-Lesson 11_L4 Variability/29. One Dimension-kPlyl6JlLjY.zh-CN.vtt 601 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-8o5Elsb2pFY.zh-CN.vtt 601 B
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.en.vtt 601 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.pt-BR.vtt 601 B
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.en.vtt 601 B
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.ar.vtt 601 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.zh-Hans.vtt 600 B
Part 09-Module 01-Lesson 03_Explore One Variable/25. Likes on the Web-stpXFmv_XrA.zh-CN.vtt 600 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.pt-BR.vtt 600 B
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.en.vtt 600 B
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.en.vtt 599 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.pt-BR.vtt 599 B
Part 13-Module 01-Lesson 04_Design Principles/16. Charts Types and Design Elements-h2tIZuzMuQU.zh-CN.vtt 599 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.hr.vtt 599 B
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.pt-BR.vtt 599 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ar.vtt 599 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.en.vtt 599 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.en.vtt 598 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.it.vtt 598 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.pt-BR.vtt 598 B
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.en.vtt 598 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.ar.vtt 597 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.ar.vtt 597 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ja.vtt 597 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.pt-BR.vtt 597 B
Part 04-Module 02-Lesson 01_Data Analysis Process/19. Lessons Completed in First Week -kL0HS6KWRcw.zh-CN.vtt 596 B
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.zh-CN.vtt 596 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.en.vtt 596 B
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.en.vtt 596 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.en.vtt 596 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-BbJfVyCm21o.zh-CN.vtt 596 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ja.vtt 596 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.es.vtt 595 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.es.vtt 595 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.ar.vtt 595 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.ar.vtt 595 B
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.en.vtt 595 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.es-ES.vtt 595 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.es.vtt 594 B
Part 09-Module 01-Lesson 05_Explore Two Variables/01. Welcome!-rkWU07ZDYzA.ja.vtt 594 B
Part 09-Module 01-Lesson 05_Explore Two Variables/27. Analyzing Two Variables-NRMKNuox9z0.zh-CN.vtt 594 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ja.vtt 594 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.pt-BR.vtt 593 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.zh-CN.vtt 593 B
Part 11-Module 01-Lesson 14_Validation/06. Where to use training vs. testing data 3-o7LnSu0CEb4.zh-CN.vtt 593 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.en-US.vtt 593 B
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.pt-BR.vtt 593 B
Part 13-Module 01-Lesson 08_Animation and Interaction/43. Delaying the Display of Buttons-783QmxtIx58.zh-CN.vtt 593 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.pt-BR.vtt 593 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.pt-BR.vtt 592 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.pt-BR.vtt 592 B
Part 09-Module 01-Lesson 02_R Basics/17. Congratulations-GxhPaVbDHnw.ja.vtt 592 B
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.en.vtt 592 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.en.vtt 591 B
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.pt-BR.vtt 591 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ar.vtt 591 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.en.vtt 591 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.zh-CN.vtt 590 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/02. Believe Results-kSyGb-QYfcU.zh-CN.vtt 590 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.pt-BR.vtt 590 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.en.vtt 590 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.en.vtt 590 B
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.en.vtt 589 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.pt-BR.vtt 589 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-dU3LgB8i6XM.zh-CN.vtt 589 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-EZTRb9VBqAc.zh-CN.vtt 589 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.pt-BR.vtt 589 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-3FO2y4tlZ3A.zh-CN.vtt 589 B
Part 11-Module 01-Lesson 09_Clustering/04. Match Points with Clusters-wJV1cRjmIYY.zh-CN.vtt 589 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.pt-BR.vtt 589 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ja.vtt 589 B
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.en.vtt 588 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.pt-BR.vtt 588 B
Part 09-Module 01-Lesson 03_Explore One Variable/04. Histogram of Users' Birthdays-mdCk7Gwkd4g.ja.vtt 588 B
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.ar.vtt 588 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/25. Transition to Tech Portion-WovqufP4nk0.zh-CN.vtt 588 B
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.en.vtt 588 B
Part 13-Module 01-Lesson 05_Dimple.js/24. Changing the X-axis Interval-WwN3tYnOd8A.zh-CN.vtt 588 B
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.en.vtt 587 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-sCZI5gWS6mg.zh-CN.vtt 587 B
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.pt-BR.vtt 587 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ja.vtt 587 B
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-fUI1XABUTrY.zh-CN.vtt 586 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-EH59aCNpHS8.zh-CN.vtt 586 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.pt-BR.vtt 586 B
Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.en.vtt 586 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.en.vtt 585 B
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.en.vtt 585 B
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.en.vtt 585 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.pt-BR.vtt 584 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.en.vtt 584 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.en-US.vtt 584 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.pt-BR.vtt 584 B
Part 11-Module 01-Lesson 13_PCA/19. Advantages of Maximal Variance-TbT6a6qaj08.zh-CN.vtt 584 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/17. Identifying Data Types-J2L_ZU-YMxc.zh-CN.vtt 584 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.en.vtt 584 B
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.pt-BR.vtt 584 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ja.vtt 584 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ar.vtt 584 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.pt-BR.vtt 584 B
Part 05-Module 02-Lesson 05_Deeper into SQL/07. Primary Keys-P1NzBPnfl2E.zh-CN.vtt 583 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.ar.vtt 583 B
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.ar.vtt 583 B
Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.pt-BR.vtt 583 B
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.en.vtt 582 B
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.pt-BR.vtt 582 B
Part 09-Module 01-Lesson 03_Explore One Variable/11. Friend Count-gydx9-h1liU.ja.vtt 582 B
Part 11-Module 01-Lesson 02_Naive Bayes/22. Unpacking NB Using Bayes Rule-lGREq530kfU.zh-CN.vtt 582 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt 582 B
Part 17-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.zh-CN.vtt 582 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.zh-CN.vtt 582 B
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.pt-BR.vtt 582 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt 582 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.pt-BR.vtt 581 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.pt-BR.vtt 581 B
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.pt-BR.vtt 581 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.en.vtt 581 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.en.vtt 581 B
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.pt-BR.vtt 581 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.pt-BR.vtt 581 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.en.vtt 580 B
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-ecy3VY8eNGM.zh-CN.vtt 580 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.pt-BR.vtt 580 B
Part 11-Module 01-Lesson 13_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.zh-CN.vtt 580 B
Part 13-Module 01-Lesson 04_Design Principles/39. Junk Yard-2CT21UEcGQk.zh-CN.vtt 580 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.es.vtt 579 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.pt-BR.vtt 579 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.es.vtt 579 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/03. Which Number to Choose-7E7Czixpviw.zh-CN.vtt 579 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-T5TBKcjzleI.zh-CN.vtt 579 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.pt-BR.vtt 579 B
Part 11-Module 01-Lesson 02_Naive Bayes/23. Bayes Rule-1biLtViOQDc.zh-CN.vtt 579 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.en.vtt 579 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.pt-BR.vtt 579 B
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.en.vtt 579 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-I_v6ueT0k3M.zh-CN.vtt 579 B
Part 13-Module 01-Lesson 08_Animation and Interaction/27. The Update Function-z5f-oK0jwZk.zh-CN.vtt 579 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-Hans.vtt 579 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.th.vtt 579 B
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.pt-BR.vtt 579 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.zh-CN.vtt 579 B
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.en.vtt 578 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.en.vtt 578 B
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.en.vtt 578 B
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.ja.vtt 578 B
Part 11-Module 01-Lesson 06_Datasets and Questions/10. Types of Data Quiz 6--LtbhZvwwM8.zh-CN.vtt 578 B
Part 13-Module 01-Lesson 04_Design Principles/46. Tabular Data versus Line Chart-9DHPaCjg9HM.zh-CN.vtt 578 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.th.vtt 578 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.pt-BR.vtt 577 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.zh-CN.vtt 577 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.pt-BR.vtt 576 B
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.pt-BR.vtt 576 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.pt-BR.vtt 575 B
Part 04-Module 02-Lesson 01_Data Analysis Process/30. Conclusion-33thdy0IjPE.zh-CN.vtt 575 B
Part 11-Module 01-Lesson 14_Validation/04. Where to use training vs. testing data 1-z2R5CqjXrkA.zh-CN.vtt 575 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt 575 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.hr.vtt 575 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.es-ES.vtt 575 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt 575 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-zlHtHBeJhww.zh-CN.vtt 574 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.en-US.vtt 574 B
Part 04-Module 02-Lesson 03_NumPy and Pandas for 2D Data/14. Adding a DataFrame to a Series-IaM7ybOda8k.zh-CN.vtt 573 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.ja.vtt 573 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.en.vtt 573 B
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.pt-BR.vtt 573 B
Part 21-Module 01-Lesson 07_Numpy Pandas - Part II/14. Adding a DataFrame to a Series-IaM7ybOda8k.zh-CN.vtt 573 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.es.vtt 572 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.en.vtt 572 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.en.vtt 572 B
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ja.vtt 572 B
Part 17-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.zh-CN.vtt 572 B
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.en.vtt 572 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/29. Blind-NNE8Cr77ytg.pt-BR.vtt 571 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/29. Blind-NNE8Cr77ytg.pt-BR.vtt 571 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/07. Meal Price t-Statistic-y1QSAIUlupg.zh-CN.vtt 571 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.pt-BR.vtt 571 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.it.vtt 571 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.en.vtt 571 B
Part 11-Module 01-Lesson 07_Regressions/09. Supervised Learning w Continuous Output-F7PIJM0q524.zh-CN.vtt 570 B
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.ar.vtt 570 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.pt-BR.vtt 570 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-9JHRpVTMuK4.zh-CN.vtt 569 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.pt-BR.vtt 569 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.en-US.vtt 569 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.en.vtt 569 B
Part 21-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.zh-CN.vtt 569 B
Part 03-Module 01-Lesson 20_L8 Estimation/24. Generalize CI-kjk--LHqtCw.zh-CN.vtt 568 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/05. DF - Add to 10-MxLG3eGzkI8.zh-CN.vtt 568 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.pt-BR.vtt 568 B
Part 11-Module 01-Lesson 04_Decision Trees/22. Information Gain Calculation Part 1-erdekkpG-Do.pt-BR.vtt 568 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/28. Rent - Find CI-1bXAy-6Pxf0.zh-CN.vtt 567 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.pt-BR.vtt 567 B
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.pt-BR.vtt 567 B
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.pt-BR.vtt 567 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.pt-BR.vtt 566 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.pt-BR.vtt 566 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.en.vtt 566 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.en.vtt 566 B
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.ar.vtt 566 B
Part 17-Module 01-Lesson 03_Admissions Case Study/01. Admissions Case Study Introduction-FGbxq1hQgtk.zh-CN.vtt 566 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.es-ES.vtt 566 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.ar.vtt 566 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-mnfgAsAVaTQ.zh-CN.vtt 565 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.en.vtt 565 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.hr.vtt 565 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.es-ES.vtt 565 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.es.vtt 564 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.es.vtt 564 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/23. Calculating Number of Pages Views Needed-ta5Nz-YCn6g.zh-CN.vtt 564 B
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.en.vtt 564 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.en.vtt 563 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.zh-CN.vtt 563 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.ar.vtt 563 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.pt-BR.vtt 563 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.pt-BR.vtt 563 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.es.vtt 562 B
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.en.vtt 562 B
Part 09-Module 01-Lesson 07_Explore Many Variables/08. Ratio Plot-gfZ7C-QBF0k.zh-CN.vtt 562 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.ar.vtt 562 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-FJjI93XvC50.zh-CN.vtt 561 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.pt-BR.vtt 561 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.en.vtt 561 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.pt-BR.vtt 561 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.ar.vtt 561 B
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.en.vtt 560 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.pt-BR.vtt 560 B
Part 11-Module 01-Lesson 13_PCA/12. Which Data is Ready for PCA-JSVsHbGUuIE.zh-CN.vtt 560 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.es-ES.vtt 560 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.en.vtt 559 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.pt-BR.vtt 559 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.pt-BR.vtt 559 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.ar.vtt 559 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.en.vtt 558 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.es.vtt 558 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-TE2BZql64XY.zh-CN.vtt 558 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.zh-CN.vtt 558 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.en.vtt 558 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ar.vtt 558 B
Part 03-Module 01-Lesson 20_L8 Estimation/08. Exact Z-Scores-8XZqX03Y6Vk.zh-CN.vtt 557 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-CZnFt1rOfwc.zh-CN.vtt 557 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.ja.vtt 557 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.pt-BR.vtt 556 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.ar.vtt 556 B
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.pt-BR.vtt 556 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-ZwMY5rAAd7Q.zh-CN.vtt 556 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-CN.vtt 556 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.pt-BR.vtt 556 B
Part 03-Module 01-Lesson 11_L4 Variability/02. Should You Get an Account-pZ_GUg7z548.zh-CN.vtt 555 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.en.vtt 555 B
Part 17-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.zh-CN.vtt 554 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.th.vtt 554 B
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.pt-BR.vtt 553 B
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.pt-BR.vtt 553 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.en.vtt 553 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.ar.vtt 553 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.zh-CN.vtt 553 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.en.vtt 553 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.zh-CN.vtt 553 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.es.vtt 552 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-kNsdYqgn9Mk.zh-CN.vtt 552 B
Part 11-Module 01-Lesson 04_Decision Trees/04. Constructing a Decision Tree First Split-GMe5JT2_oUE.zh-CN.vtt 552 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-j2SP83afRS0.zh-CN.vtt 552 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.it.vtt 552 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.pt-BR.vtt 552 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.zh-CN.vtt 552 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.en.vtt 551 B
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.en.vtt 551 B
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.pt-BR.vtt 551 B
Part 13-Module 01-Lesson 07_Narrative Structures/34. Updated World Cup Data Set-tA_je-rSL7c.zh-CN.vtt 551 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.en.vtt 550 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.en.vtt 550 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-swoZxkrxIB0.en.vtt 549 B
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.pt-BR.vtt 549 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.zh-CN.vtt 549 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ar.vtt 549 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.en.vtt 549 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.es.vtt 548 B
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.ar.vtt 548 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.th.vtt 548 B
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.en.vtt 547 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-wDjjmYJ9Z5Y.zh-CN.vtt 547 B
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.pt-BR.vtt 547 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-OrPlWwv19Jc.zh-CN.vtt 547 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-PYNWtLgtRfU.zh-CN.vtt 547 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.zh-CN.vtt 547 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ar.vtt 547 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.pt-BR.vtt 547 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.pt-BR.vtt 547 B
Part 05-Module 02-Lesson 01_Data and Tables/05. Data Meanings--laXTx9corQ.zh-CN.vtt 546 B
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.en.vtt 546 B
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.en.vtt 546 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ar.vtt 544 B
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.en.vtt 543 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.en.vtt 543 B
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.ar.vtt 543 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.ar.vtt 543 B
Part 11-Module 01-Lesson 11_Text Learning/01. Dimensions when Learning From Text-Njbmexuo7fo.zh-CN.vtt 543 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-eAN4NfHSgk8.zh-CN.vtt 542 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.ar.vtt 542 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.pt-BR.vtt 541 B
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.en.vtt 541 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.en.vtt 541 B
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.pt-BR.vtt 541 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.th.vtt 541 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.ja.vtt 541 B
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.pt-BR.vtt 541 B
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.pt-BR.vtt 541 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.es.vtt 540 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.es.vtt 540 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.en.vtt 540 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.en.vtt 540 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.pt-BR.vtt 540 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.en.vtt 540 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.pt-BR.vtt 540 B
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.pt-BR.vtt 540 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.en.vtt 540 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.pt-BR.vtt 539 B
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.ar.vtt 539 B
Part 11-Module 01-Lesson 03_SVM/08. SVM Outlier Practice-WxAO6ByCvew.zh-CN.vtt 539 B
Part 11-Module 01-Lesson 12_Feature Selection/17. Lasso Code Quiz-PlFG87qPSB4.zh-CN.vtt 539 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/02. Accuracy Review-g3sxDtlGlAM.zh-CN.vtt 539 B
Part 13-Module 01-Lesson 07_Narrative Structures/22. Narratives Summary-QFXxRlLETyI.zh-CN.vtt 539 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.hr.vtt 539 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.en.vtt 538 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.en.vtt 538 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.en.vtt 538 B
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.pt-BR.vtt 538 B
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.ar.vtt 538 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.pt-BR.vtt 538 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.zh-CN.vtt 538 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.es-ES.vtt 538 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.pt-BR.vtt 537 B
Part 05-Module 02-Lesson 01_Data and Tables/14. Primary Key-q23Nlo1Rfn4.zh-CN.vtt 537 B
Part 05-Module 02-Lesson 03_Elements of SQL/14. After Aggregating-kIITzFRh5mQ.zh-CN.vtt 537 B
Part 11-Module 01-Lesson 07_Regressions/26. Why Minimize SSE-rexAHoCGFMs.zh-CN.vtt 537 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.en.vtt 537 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.en.vtt 536 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.ar.vtt 536 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.en.vtt 536 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/08. CONCAT-bCxZnQN28Y4.zh-CN.vtt 536 B
Part 17-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.zh-CN.vtt 536 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.en.vtt 536 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.pt-BR.vtt 535 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.en.vtt 535 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.ja.vtt 535 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.ar.vtt 535 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.es-ES.vtt 535 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.ar.vtt 535 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.es.vtt 534 B
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.pt-BR.vtt 534 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.en.vtt 534 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.en.vtt 534 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-bRhdim9PTFI.zh-CN.vtt 534 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.en.vtt 534 B
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.en.vtt 534 B
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.ar.vtt 534 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.pt-BR.vtt 533 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.en.vtt 533 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.pt-BR.vtt 533 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.ar.vtt 533 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.pt-BR.vtt 533 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-HFCs3LbQ5Z0.zh-CN.vtt 533 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.ar.vtt 533 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.es-ES.vtt 533 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.pt-BR.vtt 533 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/11. Bounds of Area-eADm6bXU3_0.zh-CN.vtt 532 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.ar.vtt 532 B
Part 13-Module 01-Lesson 04_Design Principles/44. Leland Wilkinson-w7TLo_X4sfY.zh-CN.vtt 532 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.ja.vtt 532 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.ar.vtt 532 B
Part 17-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.zh-CN.vtt 532 B
Part 17-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.zh-CN.vtt 532 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.en.vtt 531 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.en.vtt 531 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.en.vtt 531 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.pt-BR.vtt 531 B
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.zh-CN.vtt 531 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.ar.vtt 531 B
Part 17-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.zh-CN.vtt 531 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ja.vtt 531 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.es-ES.vtt 531 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.es.vtt 530 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.pt-BR.vtt 530 B
Part 11-Module 01-Lesson 09_Clustering/13. Some challenges of k-means-e2CdlG5P4WA.zh-CN.vtt 530 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.hr.vtt 530 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.pt-BR.vtt 530 B
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.en.vtt 530 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.nl.vtt 529 B
Part 03-Module 01-Lesson 11_L4 Variability/12. Define Outlier-jxatUS0YvtU.zh-CN.vtt 529 B
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.en.vtt 529 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.pt-BR.vtt 529 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.ar.vtt 529 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ziYBjY1kTC8.zh-CN.vtt 529 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.pt-BR.vtt 529 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.es-ES.vtt 529 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.pt-BR.vtt 529 B
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.en.vtt 528 B
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.pt-BR.vtt 528 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-a2GCyz_N0oY.zh-CN.vtt 528 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/07. How Does Your Algorithm Compare-B2KnUg5iz0Y.zh-CN.vtt 528 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/11. Repeating the Experiment-HH73nOnzRrc.zh-CN.vtt 528 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.en.vtt 528 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.pt-BR.vtt 527 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.ja.vtt 527 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.en.vtt 527 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ja.vtt 527 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.pt-BR.vtt 526 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.pt-BR.vtt 526 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/02. Gambling in Vegas-qbcBbbm3lt8.zh-CN.vtt 526 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.en.vtt 526 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.en.vtt 526 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-TpVxnYcI_uw.zh-CN.vtt 526 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.pt-BR.vtt 526 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.ar.vtt 526 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.pt-BR.vtt 526 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ja.vtt 525 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.pt-BR.vtt 524 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.en.vtt 524 B
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.pt-BR.vtt 524 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.ar.vtt 524 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.en.vtt 524 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.en.vtt 523 B
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.en.vtt 523 B
Part 03-Module 01-Lesson 11_L4 Variability/20. Equation for Average Deviation-9jdZ9pfYP6A.zh-CN.vtt 523 B
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.pt-BR.vtt 523 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.en.vtt 523 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.pt-BR.vtt 523 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.en.vtt 523 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.pt-BR.vtt 523 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.pt-BR.vtt 523 B
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.pt-BR.vtt 522 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.en.vtt 522 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-PXDcczTlqLc.zh-CN.vtt 522 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.pt-BR.vtt 522 B
Part 14-Module 01-Lesson 01_Overview of AB Testing/17. Null and Alternative Hypothesis-BGNx2FiNFY0.zh-CN.vtt 522 B
Part 16-Module 03-Lesson 06_[Advanced] SQL Window Functions/23. Window Functions Conclusion-2ZdocDMw7D8.pt-BR.vtt 522 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.zh-CN.vtt 522 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.zh-CN.vtt 522 B
Part 03-Module 01-Lesson 02_PS 1a Intro to Research Methods/18. 26. Video Games-SyszPG1615c.zh-CN.vtt 521 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.ar.vtt 521 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.ar.vtt 521 B
Part 13-Module 01-Lesson 04_Design Principles/53. Grammar of Graphics Pipeline and D3-eVAEO2QRdM0.zh-CN.vtt 521 B
Part 17-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1--TBAfU1cjRU.zh-CN.vtt 521 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.pt-BR.vtt 520 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.pt-BR.vtt 520 B
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.zh-CN.vtt 519 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.en.vtt 518 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.en.vtt 518 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.es.vtt 518 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.pt-BR.vtt 518 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/06. DF - Marginal Totals-ykVKAjC9_TA.zh-CN.vtt 518 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.en.vtt 518 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.pt-BR.vtt 518 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.en.vtt 518 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.ar.vtt 518 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.ar.vtt 518 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.es.vtt 517 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.es.vtt 517 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.en.vtt 517 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/07. Sampling Distribution-kQevFvu_dL0.zh-CN.vtt 517 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.en.vtt 517 B
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.pt-BR.vtt 517 B
Part 17-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.hr.vtt 517 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.en.vtt 516 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-dxw2VFq5sAc.zh-CN.vtt 516 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.zh-CN.vtt 516 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.pt-BR.vtt 516 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ar.vtt 516 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.es-ES.vtt 516 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.en.vtt 515 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.en.vtt 515 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.pt-BR.vtt 515 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.ar.vtt 515 B
Part 03-Module 01-Lesson 11_L4 Variability/04. Quantify Spread-hAPJsh81L98.zh-CN.vtt 514 B
Part 01-Module 01-Lesson 01_Nanodegree Orientation/02. Introduction-fxNSn63xFvA.zh-CN.vtt 513 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-Khxyqd5vtOo.zh-CN.vtt 513 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.pt-BR.vtt 513 B
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.en.vtt 513 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.pt-BR.vtt 513 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.en.vtt 513 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.en.vtt 513 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.zh-CN.vtt 512 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/13. Sleep and Memory-9DARTybbf1c.zh-CN.vtt 512 B
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-XP3F26GGuhE.zh-CN.vtt 512 B
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.ar.vtt 512 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.en.vtt 512 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.ar.vtt 511 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.ar.vtt 511 B
Part 11-Module 01-Lesson 07_Regressions/05. Email Author Continuous or Discrete-GD9Bpjm31co.zh-CN.vtt 510 B
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.ar.vtt 510 B
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.en.vtt 510 B
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.pt-BR.vtt 510 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.zh-CN.vtt 509 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-q413Zzil8lQ.zh-CN.vtt 509 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ar.vtt 509 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.pt-BR.vtt 508 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.pt-BR.vtt 508 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.pt-BR.vtt 508 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/25. Congratulations and Next Steps-ph4p8n-I7vw.zh-CN.vtt 508 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.zh-CN.vtt 508 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.ar.vtt 508 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.en.vtt 508 B
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.pt-BR.vtt 508 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.en.vtt 507 B
Part 11-Module 01-Lesson 02_Naive Bayes/15. Transition to Using Naive Bayes-2_dJXh1qqe0.en.vtt 507 B
Part 11-Module 01-Lesson 10_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.zh-CN.vtt 507 B
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.pt-BR.vtt 507 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.en.vtt 507 B
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.pt-BR.vtt 506 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.pt-BR.vtt 505 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.pt-BR.vtt 505 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.pt-BR.vtt 505 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.ar.vtt 505 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/09. Confusion Matrix False Alarms-611qWzIxGmU.zh-CN.vtt 505 B
Part 17-Module 01-Lesson 16_Logistic Regression/14. Confusion Matrix False Alarms-611qWzIxGmU.zh-CN.vtt 505 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.en.vtt 504 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-OIxLJeZ_jNI.zh-CN.vtt 504 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.ar.vtt 504 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.it.vtt 504 B
Part 17-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.zh-CN.vtt 504 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.es.vtt 503 B
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.pt-BR.vtt 503 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.pt-BR.vtt 503 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/29. Congrats-psVUIDdsbA0.zh-CN.vtt 503 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/23. Equation for Precision-CStZqZRe6Mk.zh-CN.vtt 503 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.en.vtt 503 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.pt-BR.vtt 503 B
Part 17-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.zh-CN.vtt 503 B
Part 19-Module 01-Lesson 01_Introduction to Data Visualization/05. Data Types Review-xzZZZCZk5YM.zh-CN.vtt 503 B
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.pt-BR.vtt 502 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.en.vtt 502 B
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.en.vtt 502 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-Xrl2Hd--NWs.zh-CN.vtt 502 B
Part 13-Module 01-Lesson 04_Design Principles/21. Negative Space and Cholera-VEXUQmVpazE.zh-CN.vtt 502 B
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.en.vtt 502 B
Part 13-Module 01-Lesson 08_Animation and Interaction/21. Sizing Circles for Attendance-5cs9badCyPQ.zh-CN.vtt 502 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.es-ES.vtt 502 B
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.en.vtt 501 B
Part 09-Module 01-Lesson 05_Explore Two Variables/19. Noisy Scatterplots-k_mm11ePWpg.ja.vtt 501 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.ar.vtt 501 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.pt-BR.vtt 501 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.en.vtt 500 B
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.pt-BR.vtt 500 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.pt-BR.vtt 500 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.pt-BR.vtt 499 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.pt-BR.vtt 499 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-Kn9v0KGDsvc.zh-CN.vtt 499 B
Part 11-Module 01-Lesson 13_PCA/14. Measurable vs. Latent Features Quiz-20QVVrTcp2A.zh-CN.vtt 499 B
Part 17-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.zh-CN.vtt 499 B
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.pt-BR.vtt 498 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.pt-BR.vtt 498 B
Part 11-Module 01-Lesson 13_PCA/17. Composite Features-0ZBp8oWySAc.zh-CN.vtt 498 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.pt-BR.vtt 498 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.es.vtt 497 B
Part 03-Module 01-Lesson 20_L8 Estimation/17. Find 98 CI-guhmjr4BqSo.zh-CN.vtt 497 B
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.pt-BR.vtt 497 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-cUhgZ2BnWq0.zh-CN.vtt 497 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.pt-BR.vtt 497 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.en.vtt 497 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.pt-BR.vtt 497 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ar.vtt 497 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.pt-BR.vtt 496 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/02. Action Time-80DSWU8ZUoQ.zh-CN.vtt 496 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.ar.vtt 496 B
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.pt-BR.vtt 496 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.pt-BR.vtt 496 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.en.vtt 496 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.zh-CN.vtt 495 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/17. Sample Average-lR1rf2NQ6_M.zh-CN.vtt 495 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.en.vtt 495 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/18. Conclusion-P7H8wjCIJ6k.zh-CN.vtt 495 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.en.vtt 495 B
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.en.vtt 495 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.ar.vtt 495 B
Part 17-Module 01-Lesson 04_Probability/08. Two Flips 1-yUIz7SgUwJg.en.vtt 495 B
Part 17-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.zh-CN.vtt 495 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.pt-BR.vtt 495 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.en.vtt 495 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/19. Conclusion-P7H8wjCIJ6k.zh-CN.vtt 495 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.es.vtt 494 B
Part 03-Module 01-Lesson 11_L4 Variability/09. Q3 - Q1-tYaQItpvXUo.zh-CN.vtt 494 B
Part 03-Module 01-Lesson 20_L8 Estimation/04. Percent of Sample Means-kuTOS0wZJd4.zh-CN.vtt 494 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.pt-BR.vtt 494 B
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.ja.vtt 494 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.ar.vtt 494 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.pt-BR.vtt 494 B
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.en.vtt 494 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.pt-BR.vtt 493 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ar.vtt 493 B
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.es-ES.vtt 493 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.pt-BR.vtt 493 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.pt-BR.vtt 492 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.es.vtt 492 B
Part 03-Module 01-Lesson 13_L5 Standardizing/24. Convert to Popularity Score--Sw8Dlo0fx4.zh-CN.vtt 492 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/02. Probability-Wf7m7ygRvz8.zh-CN.vtt 492 B
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.pt-BR.vtt 492 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-lmuonrQp_lM.zh-CN.vtt 492 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ja.vtt 492 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.pt-BR.vtt 491 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.pt-BR.vtt 491 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.en.vtt 491 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ar.vtt 491 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ja.vtt 491 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.en.vtt 491 B
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.pt-BR.vtt 490 B
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.ar.vtt 490 B
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.ar.vtt 490 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.en.vtt 490 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-n7gp8USw0Jw.zh-CN.vtt 490 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.zh-CN.vtt 490 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.ar.vtt 489 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.pt-BR.vtt 489 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/20. P-Value-qrN5FQdm9uA.zh-CN.vtt 489 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.pt-BR.vtt 489 B
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.en.vtt 489 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/14. -E-Bd6EEl20s.zh-CN.vtt 489 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.pt-BR.vtt 488 B
Part 11-Module 01-Lesson 09_Clustering/05. Optimizing Centers (Rubber Bands)-TN1rQMrx65c.zh-CN.vtt 488 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.pt-BR.vtt 488 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.pt-BR.vtt 488 B
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.ja.vtt 487 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.zh-CN.vtt 486 B
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.pt-BR.vtt 486 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.en.vtt 486 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.pt-BR.vtt 486 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.en.vtt 486 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.pt-BR.vtt 485 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.pt-BR.vtt 485 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/17. Find Standard Error-ctx--oGjVgs.zh-CN.vtt 485 B
Part 11-Module 01-Lesson 02_Naive Bayes/13. From Scatterplots to Decision Surfaces-DLCq1-kOGX0.zh-CN.vtt 485 B
Part 11-Module 01-Lesson 05_Choose Your Own Algorithm/09. L4_Mini Project-CGPO68cOCgc.zh-CN.vtt 485 B
Part 11-Module 01-Lesson 13_PCA/27. PCA on the Enron Finance Data-6ufIq2nrTwg.zh-CN.vtt 485 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.en.vtt 484 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.pt-BR.vtt 484 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.zh-CN.vtt 484 B
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.en.vtt 484 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/13. SD of Sampling Distribution-rJ8NsbL5iTk.zh-CN.vtt 483 B
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.pt-BR.vtt 483 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.pt-BR.vtt 483 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.pt-BR.vtt 483 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.en.vtt 483 B
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.ar.vtt 483 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/16. -6-NsyLPx738.zh-CN.vtt 483 B
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.en.vtt 483 B
Part 13-Module 01-Lesson 04_Design Principles/49. Advantages of the Grammar of Graphics-l7P-e1M_qPA.zh-CN.vtt 483 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.ja.vtt 483 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.ar.vtt 482 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.ar.vtt 482 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.en.vtt 482 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.en-US.vtt 482 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.pt-BR.vtt 482 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.en-US.vtt 482 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.pt-BR.vtt 482 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.ar.vtt 482 B
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.en.vtt 481 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.ar.vtt 481 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.pt-BR.vtt 481 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-FNKRumSym18.zh-CN.vtt 480 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.pt-BR.vtt 480 B
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.ar.vtt 480 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.es-ES.vtt 480 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.th.vtt 480 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/14. Histogram-xE00wGLivN4.zh-CN.vtt 479 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.en.vtt 479 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-xBnhUJENAtk.zh-CN.vtt 479 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.en.vtt 479 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.ar.vtt 479 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.ar.vtt 479 B
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.en.vtt 479 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.en.vtt 479 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/03. US, China, Pakistan-6K9Zztqbozw.zh-CN.vtt 478 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions-szqkEhERjDI.zh-CN.vtt 478 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.en.vtt 478 B
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.ja.vtt 478 B
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.pt-BR.vtt 478 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.pt-BR.vtt 478 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.es-ES.vtt 478 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.pt-BR.vtt 478 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.en.vtt 477 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/12. Ratio of SDs-E14J3Thd0lc.zh-CN.vtt 476 B
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.en.vtt 476 B
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.ja.vtt 476 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.ar.vtt 476 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.it.vtt 476 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.pt-BR.vtt 475 B
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.pt-BR.vtt 474 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.ar.vtt 474 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.ar.vtt 474 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.pt-BR.vtt 474 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.en.vtt 473 B
Part 05-Module 02-Lesson 03_Elements of SQL/15. More JOIN Practice-bnwLadF8gKo.zh-CN.vtt 473 B
Part 07-Module 01-Lesson 01_GitHub Review/11. Reflect on your commit messages-_0AHmKkfjTo.zh-CN.vtt 473 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.en.vtt 473 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.ar.vtt 473 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.en.vtt 473 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.es-ES.vtt 473 B
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.ja.vtt 473 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.pt-BR.vtt 473 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ar.vtt 473 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ar.vtt 473 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.pt-BR.vtt 473 B
Part 17-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.zh-CN.vtt 473 B
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.en.vtt 473 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-l7p3uldaCks.zh-CN.vtt 472 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.pt-BR.vtt 472 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.ja.vtt 472 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.ja.vtt 472 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.en.vtt 472 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.en.vtt 472 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.en-US.vtt 472 B
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.pt-BR.vtt 472 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/16. Cleaning Data-AJF5smH1TJU.zh-CN.vtt 472 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ar.vtt 472 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.en-US.vtt 472 B
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.pt-BR.vtt 471 B
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.en.vtt 471 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.ar.vtt 471 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.es-ES.vtt 471 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.es-ES.vtt 471 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.ar.vtt 471 B
Part 11-Module 01-Lesson 03_SVM/14. Nonlinear Data-PxE2bbG2Hkw.en.vtt 470 B
Part 11-Module 01-Lesson 11_Text Learning/09. Getting Stopwords from NLTK-R0RqC-yerD4.zh-CN.vtt 470 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.en.vtt 470 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.es.vtt 469 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-NcWS_BvM3IU.zh-CN.vtt 469 B
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.en.vtt 469 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.en.vtt 469 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.en.vtt 469 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.pt-BR.vtt 469 B
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.zh-CN.vtt 469 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.ja.vtt 469 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.en.vtt 469 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.hr.vtt 469 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.en.vtt 469 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.pt-BR.vtt 468 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.en.vtt 468 B
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.en.vtt 468 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.en.vtt 468 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.en.vtt 468 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.en.vtt 468 B
Part 03-Module 01-Lesson 03_PS 1b Additional Practice (Optional)/09. 25. Caffeine--D3nyKUK1kY.zh-CN.vtt 467 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.ko.vtt 467 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-Jbqf8OBORDg.zh-CN.vtt 467 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-Jbqf8OBORDg.zh-CN.vtt 467 B
Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.en.vtt 467 B
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.en.vtt 466 B
Part 03-Module 01-Lesson 13_L5 Standardizing/22. Popular Chris-VTgnBeCqHjE.zh-CN.vtt 466 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.ja.vtt 466 B
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.ja.vtt 466 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.ar.vtt 466 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.es-ES.vtt 466 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.pt-BR.vtt 465 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.en.vtt 464 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.pt-BR.vtt 464 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.pt-BR.vtt 464 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.ar.vtt 464 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.en.vtt 464 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.en.vtt 464 B
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.en-US.vtt 463 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ar.vtt 463 B
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-eLyI7n6GtbU.zh-CN.vtt 462 B
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.en.vtt 462 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.en.vtt 462 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.en.vtt 462 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.en.vtt 462 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.ar.vtt 462 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.ar.vtt 462 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-5tdFjuAX9u0.zh-CN.vtt 461 B
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.en.vtt 461 B
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.pt-BR.vtt 461 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.en.vtt 461 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.ja.vtt 461 B
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.pt-BR.vtt 461 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.en.vtt 461 B
Part 03-Module 01-Lesson 11_L4 Variability/01. Social Networkers' Salaries-4nYdxMABeBc.zh-CN.vtt 460 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.en.vtt 460 B
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.en.vtt 460 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.pt-BR.vtt 460 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.zh-CN.vtt 460 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.zh-CN.vtt 460 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.en.vtt 459 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.ar.vtt 459 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ar.vtt 459 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.es-ES.vtt 459 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.es-ES.vtt 458 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.es-ES.vtt 458 B
Part 09-Module 01-Lesson 03_Explore One Variable/01. Welcome!-cCOHhYXU6G0.zh-CN.vtt 458 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.en.vtt 458 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.ar.vtt 458 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.en.vtt 458 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.en.vtt 458 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.ja.vtt 458 B
Part 17-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.zh-CN.vtt 458 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.pt-BR.vtt 457 B
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.pt-BR.vtt 457 B
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.pt-BR.vtt 457 B
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.en.vtt 457 B
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.en.vtt 456 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.en.vtt 456 B
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.pt-BR.vtt 456 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.pt-BR.vtt 456 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.zh-CN.vtt 456 B
Part 13-Module 01-Lesson 05_Dimple.js/22. Interactivity is Simple with Dimple-_itWo-gUTzY.zh-CN.vtt 456 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.it.vtt 456 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ar.vtt 456 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.zh-CN.vtt 456 B
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.ar.vtt 456 B
Part 21-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.zh-CN.vtt 456 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/22. Find Median with Outlier-RIJpz1jXO4A.zh-CN.vtt 455 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.en.vtt 455 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.pt-BR.vtt 455 B
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.en.vtt 455 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.ar.vtt 455 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.es-ES.vtt 455 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.en.vtt 455 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.ar.vtt 455 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/02. Frequency-2yo4xrFnDyg.zh-CN.vtt 454 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.pt-BR.vtt 454 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.pt-BR.vtt 454 B
Part 11-Module 01-Lesson 07_Regressions/22. Error Quiz-O5B-Z5SUoc8.zh-CN.vtt 454 B
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.pt-BR.vtt 454 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.pt-BR.vtt 454 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.es.vtt 453 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.pt-BR.vtt 453 B
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.pt-BR.vtt 453 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.en.vtt 453 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.hr.vtt 453 B
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.en.vtt 453 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.es.vtt 452 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.es.vtt 452 B
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-1K7_1uPm8F8.zh-CN.vtt 452 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.en.vtt 452 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-SyNQ2mElRi0.zh-CN.vtt 452 B
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.pt-BR.vtt 452 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.ar.vtt 452 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.en.vtt 452 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.it.vtt 452 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/09. Operational Definition-khRQslIcqyY.zh-CN.vtt 451 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/09. Operational Definition-khRQslIcqyY.zh-CN.vtt 451 B
Part 03-Module 01-Lesson 11_L4 Variability/26. Sum of Squares-Vr3knoVJvlk.zh-CN.vtt 451 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.en.vtt 451 B
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.ja.vtt 451 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.pt-BR.vtt 451 B
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.en.vtt 451 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/14. Classifying Chavez Correctly 1-0PFq8zoaNWU.zh-CN.vtt 451 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.es-ES.vtt 451 B
Part 17-Module 01-Lesson 16_Logistic Regression/18. Classifying Chavez Correctly 1-0PFq8zoaNWU.zh-CN.vtt 451 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.en.vtt 450 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.en.vtt 450 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.en.vtt 450 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.ja.vtt 450 B
Part 13-Module 01-Lesson 04_Design Principles/32. Do No Harm-BIQPOMfDXjs.zh-CN.vtt 450 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.pt-BR.vtt 449 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.en-US.vtt 449 B
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.en.vtt 449 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.en.vtt 449 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.ja.vtt 449 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.en.vtt 449 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.pt-BR.vtt 448 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.es.vtt 447 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.pt-BR.vtt 447 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.ar.vtt 447 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.pt-BR.vtt 447 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.ar.vtt 447 B
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.ar.vtt 447 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.pt-BR.vtt 447 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.th.vtt 447 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.en.vtt 446 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.ar.vtt 446 B
Part 16-Module 03-Lesson 04_SQL Subqueries Temporary Tables/16. Subquery Conclusion-TUYvx2K9-5k.zh-CN.vtt 446 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.pt-BR.vtt 445 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.en.vtt 445 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.pt-BR.vtt 445 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.en.vtt 445 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.pt-BR.vtt 445 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ar.vtt 445 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.en.vtt 444 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.pt-BR.vtt 444 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.en.vtt 444 B
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.en.vtt 444 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.ar.vtt 444 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.it.vtt 444 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.ja.vtt 444 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.pt-BR.vtt 444 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.en.vtt 443 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.en.vtt 443 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-U2yZxIeG2t0.ja.vtt 443 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.en.vtt 442 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.en.vtt 442 B
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.pt-BR.vtt 442 B
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.pt-BR.vtt 442 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.pt-BR.vtt 442 B
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.en.vtt 442 B
Part 17-Module 01-Lesson 02_Descriptive Statistics - Part II/31. Descriptive Statistics Summary-Fe7Gta2SfLA.zh-CN.vtt 442 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.pt-BR.vtt 442 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.es.vtt 441 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.es.vtt 441 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.pt-BR.vtt 441 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.pt-BR.vtt 441 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.th.vtt 441 B
Part 17-Module 01-Lesson 08_Python Probability Practice/01. Python Probability Introduction-tFMdvAN7WDY.zh-CN.vtt 441 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.pt-BR.vtt 440 B
Part 05-Module 02-Lesson 03_Elements of SQL/02. Talk to the Zoo Database-9AVeGkUcPYQ.zh-CN.vtt 440 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.en.vtt 440 B
Part 11-Module 01-Lesson 13_PCA/09. Second Principal Component Of New System-cTjBlM2ATLQ.zh-CN.vtt 440 B
Part 16-Module 03-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.zh-CN.vtt 440 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.pt-BR.vtt 440 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.en.vtt 439 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.en.vtt 439 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.en.vtt 439 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.en.vtt 439 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.en.vtt 439 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.pt-BR.vtt 439 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.pt-BR.vtt 439 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.es.vtt 438 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.es.vtt 438 B
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.en.vtt 438 B
Part 07-Module 01-Lesson 01_GitHub Review/12. Participating in open source projects-OxL-gMTizUA.zh-CN.vtt 438 B
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.ar.vtt 438 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.zh-CN.vtt 437 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.en.vtt 437 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.en.vtt 437 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.en.vtt 437 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ar.vtt 437 B
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.en.vtt 436 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/18. More than 20-W0R3XOK1IfE.zh-CN.vtt 436 B
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.en.vtt 436 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.pt-BR.vtt 436 B
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.ar.vtt 436 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ar.vtt 436 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-vsID16a_suU.zh-CN.vtt 435 B
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.pt-BR.vtt 435 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-wDRJK3htUZE.zh-CN.vtt 435 B
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.en.vtt 435 B
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.en.vtt 435 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.pt-BR.vtt 435 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.it.vtt 435 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/13. Visualizing Data-tqXBhXfWiDE.en.vtt 434 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.hi.vtt 434 B
Part 11-Module 01-Lesson 02_Naive Bayes/33. Posterior Probabilities-lJlS-Xdlu5o.ja.vtt 434 B
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.zh-CN.vtt 434 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.zh-CN.vtt 434 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.pt-BR.vtt 433 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.en.vtt 433 B
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-mVBWg3aPPhI.zh-CN.vtt 433 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.en.vtt 433 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.ja.vtt 433 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.pt-BR.vtt 433 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.en.vtt 433 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.it.vtt 433 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.pt-BR.vtt 433 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.pt-BR.vtt 432 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.pt-BR.vtt 432 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.zh-CN.vtt 432 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.ja.vtt 432 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.pt-BR.vtt 432 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/01. Communicating with your data-KDnca1zszIo.zh-CN.vtt 432 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.en.vtt 432 B
Part 19-Module 01-Lesson 04_Making Dashboards Stories in Tableau/01. Communicating With Your Data-KDnca1zszIo.zh-CN.vtt 432 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/23. Difference Between Graphs-1jUwuW70lF0.zh-CN.vtt 431 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/16. Fail to Reject the Null-qUcZFxEXz2I.zh-CN.vtt 431 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.en.vtt 431 B
Part 05-Module 02-Lesson 05_Deeper into SQL/19. Outro-q7a9w02Uepw.pt-BR.vtt 431 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.ja.vtt 431 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.ar.vtt 431 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.zh-CN.vtt 431 B
Part 03-Module 01-Lesson 11_L4 Variability/08. Where Is Q1-0ZTaV6UATBI.zh-CN.vtt 430 B
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.en.vtt 430 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-c6PzC3WZD4I.zh-CN.vtt 430 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.en.vtt 430 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.zh-CN.vtt 430 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/13. Series Indexes-FA4mkuoDoJI.zh-CN.vtt 430 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.en.vtt 430 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/14. Series Indexes-FA4mkuoDoJI.zh-CN.vtt 430 B
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.en.vtt 429 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/10. Two-Tailed t-Test-5mxtx0yqlyM.zh-CN.vtt 429 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-QyKOEh0722A.zh-CN.vtt 429 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.pt-BR.vtt 429 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.en.vtt 428 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.en.vtt 428 B
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.en.vtt 428 B
Part 15-Module 01-Lesson 03_Creating Visualizations in Tableau/23. L3 outro-y46uDftUXHo.en.vtt 428 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.en.vtt 428 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ja.vtt 428 B
Part 19-Module 01-Lesson 03_Data Visualizations in Tableau/47. What's Next-y46uDftUXHo.en.vtt 428 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.en.vtt 427 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.en.vtt 427 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.pt-BR.vtt 427 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.pt-BR.vtt 427 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.pt-BR.vtt 427 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.pt-BR.vtt 427 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.en.vtt 427 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.en.vtt 426 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.en.vtt 426 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.pt-BR.vtt 426 B
Part 09-Module 01-Lesson 07_Explore Many Variables/01. Multivariate Data-jsg6lhrJN1g.zh-CN.vtt 426 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price-Ck4i1Yk4pT0.zh-CN.vtt 426 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.pt-BR.vtt 426 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-bxDutNyYKjE.zh-CN.vtt 426 B
Part 13-Module 01-Lesson 05_Dimple.js/25. Bar Chart Issues-MNsMZH1Y0Js.zh-CN.vtt 426 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.es-ES.vtt 426 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-bxDutNyYKjE.zh-CN.vtt 426 B
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.pt-BR.vtt 425 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.en.vtt 425 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.ja.vtt 425 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-oWyt6md7P44.zh-CN.vtt 425 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.ar.vtt 425 B
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.ar.vtt 425 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-Lb_v4vj3TNs.zh-CN.vtt 425 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.hr.vtt 425 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.en.vtt 425 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.es-ES.vtt 425 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-Lb_v4vj3TNs.zh-CN.vtt 425 B
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.pt-BR.vtt 424 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.ja.vtt 424 B
Part 11-Module 01-Lesson 09_Clustering/09. K-Means Cluster Visualization-ZMfwPUrOFsE.zh-CN.vtt 424 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.es-ES.vtt 424 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.en.vtt 424 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.es.vtt 423 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-u6vw-FcHT-M.pt-BR.vtt 423 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.en.vtt 423 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.ar.vtt 423 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.ar.vtt 423 B
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.pt-BR.vtt 423 B
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.ar.vtt 423 B
Part 15-Module 01-Lesson 04_Telling Stories with Tableau/08. Further Learning-SnLQlP5J7c8.zh-CN.vtt 423 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.th.vtt 423 B
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.en.vtt 423 B
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.pt-BR.vtt 422 B
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-seTkSLAS43o.zh-CN.vtt 422 B
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.en.vtt 422 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.ar.vtt 422 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.en.vtt 422 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-q4c5n5W2aUc.zh-CN.vtt 422 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.ar.vtt 422 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.zh-CN.vtt 422 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.it.vtt 422 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.pt-BR.vtt 422 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.ar.vtt 422 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.pt-BR.vtt 421 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.pt-BR.vtt 421 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.en.vtt 421 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.pt-BR.vtt 421 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.pt-BR.vtt 421 B
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.ar.vtt 421 B
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.en.vtt 421 B
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.pt-BR.vtt 421 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.en.vtt 420 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-yexyfs5ca2k.zh-CN.vtt 420 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.pt-BR.vtt 420 B
Part 11-Module 01-Lesson 04_Decision Trees/31. Information Gain Calculation Part 10-XYHTuv2FpWQ.zh-CN.vtt 420 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ar.vtt 420 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ja.vtt 420 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.zh-CN.vtt 420 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.pt-BR.vtt 420 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.pt-BR.vtt 419 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.pt-BR.vtt 419 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.en.vtt 419 B
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.ar.vtt 419 B
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.en.vtt 419 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.ar.vtt 419 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.ja.vtt 419 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.en.vtt 418 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.en.vtt 418 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.pt-BR.vtt 418 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.zh-CN.vtt 417 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/27. Downsides of Surveys-mFV4DJuEFhQ.zh-CN.vtt 417 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.pt-BR.vtt 417 B
Part 03-Module 01-Lesson 11_L4 Variability/28. Avg. Squared Dev. in Words--_I23DcNTF0.zh-CN.vtt 417 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.en.vtt 417 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/03. Tetrahedral Die-WtGcIl_o_40.zh-CN.vtt 417 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.pt-BR.vtt 417 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.pt-BR.vtt 417 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.pt-BR.vtt 417 B
Part 13-Module 01-Lesson 07_Narrative Structures/31. enter() and exit()-4EpW5acw55c.zh-CN.vtt 417 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.es-ES.vtt 417 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ja.vtt 417 B
Part 09-Module 01-Lesson 07_Explore Many Variables/04. Plotting Conditional Summaries-8SqL0v_FSsc.zh-CN.vtt 416 B
Part 11-Module 01-Lesson 02_Naive Bayes/19. GaussianNB Deployment on Terrain Data-TcSnd3_hAy8.zh-CN.vtt 416 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.ja.vtt 416 B
Part 15-Module 01-Lesson 02_Design Principles/20. Onwards!-i-ulsdVHhCc.zh-CN.vtt 416 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.en.vtt 416 B
Part 19-Module 01-Lesson 02_Design/22. Onwards!-i-ulsdVHhCc.zh-CN.vtt 416 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.en.vtt 415 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.pt-BR.vtt 415 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-KD_AqWVG4Cc.zh-CN.vtt 415 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.pt-BR.vtt 415 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.pt-BR.vtt 415 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.en.vtt 415 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.en.vtt 415 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.pt-BR.vtt 415 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-f_SBhjbfmPw.zh-CN.vtt 415 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ja.vtt 415 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.th.vtt 415 B
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.en.vtt 414 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.pt-BR.vtt 414 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-e_8DmUBHAao.zh-CN.vtt 414 B
Part 11-Module 01-Lesson 08_Outliers/05. Outlier Detection Using Residual Errors-ZlDdxWYv6jw.zh-CN.vtt 414 B
Part 15-Module 01-Lesson 01_Data Visualization Fundamentals/21. Visualization design -TTGYKv5Qta0.zh-CN.vtt 414 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.it.vtt 414 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.en.vtt 414 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.pt-BR.vtt 413 B
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.pt-BR.vtt 413 B
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.en.vtt 413 B
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-oV8f7eO_1hA.zh-CN.vtt 413 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-kKT56up4n_o.zh-CN.vtt 413 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.en.vtt 413 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.ar.vtt 413 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.pt-BR.vtt 412 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/01. Welcome to Lesson 2-53b_nnGcnBY.en.vtt 412 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.en.vtt 412 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.ar.vtt 412 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.es-ES.vtt 412 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.en.vtt 411 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-yejk0jbkWBk.zh-CN.vtt 411 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ar.vtt 411 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.zh-CN.vtt 411 B
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.pt-BR.vtt 411 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.en.vtt 410 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/02. Guinness-6V5K3VOGp8c.zh-CN.vtt 410 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-4FAowd-l1p4.zh-CN.vtt 410 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.pt-BR.vtt 410 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.pt-BR.vtt 410 B
Part 07-Module 01-Lesson 01_GitHub Review/07. Quick Fixes #2-It6AEuSDQw0.zh-CN.vtt 410 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.ja.vtt 410 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.pt-BR.vtt 410 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.ar.vtt 410 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.pt-BR.vtt 410 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.pt-BR.vtt 410 B
Part 21-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.zh-CN.vtt 410 B
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.pt-BR.vtt 409 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/39. Keyboards - CI for Dependent Samples-POKBAWQ2S7U.zh-CN.vtt 409 B
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.en.vtt 409 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.zh-CN.vtt 409 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-V-jzhJoeZj8.zh-CN.vtt 409 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/25. Communicating Results-tmAlVZCbgFA.zh-CN.vtt 409 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.it.vtt 409 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.en.vtt 408 B
Part 03-Module 01-Lesson 11_L4 Variability/11. What Is an Outlier-GRLrzWwTz58.en.vtt 408 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.pt-BR.vtt 408 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.pt-BR.vtt 408 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.en.vtt 408 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-WDADret_QqE.zh-CN.vtt 408 B
Part 11-Module 01-Lesson 13_PCA/13. When Does an Axis Dominate-4hJlaYRHdpA.zh-CN.vtt 408 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.ar.vtt 408 B
Part 17-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.zh-CN.vtt 408 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.zh-CN.vtt 408 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.ar.vtt 408 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.pt-BR.vtt 407 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.pt-BR.vtt 407 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.pt-BR.vtt 407 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-b7oUjvNJWCc.zh-CN.vtt 407 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.en.vtt 407 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.pt-BR.vtt 406 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.en.vtt 406 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.en.vtt 406 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.ar.vtt 406 B
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.en.vtt 406 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.pt-BR.vtt 406 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.es-ES.vtt 406 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.pt-BR.vtt 406 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.en-US.vtt 405 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/07. Proportion of Facebook Friends-swOg73wqLKM.zh-CN.vtt 405 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/35. Increase Sample Size-VXH1be4d1Nc.zh-CN.vtt 405 B
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.en.vtt 405 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.pt-BR.vtt 405 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.pt-BR.vtt 405 B
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.pt-BR.vtt 405 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.en.vtt 405 B
Part 11-Module 01-Lesson 12_Feature Selection/18. Lasso Prediction with sklearn Quiz-v2_aFAmQxfw.zh-CN.vtt 405 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.pt-BR.vtt 405 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ar.vtt 405 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.pt-BR.vtt 405 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-Adzhg-M3Pvk.pt-BR.vtt 404 B
Part 11-Module 01-Lesson 04_Decision Trees/09. [object Object]-i7pRvuVoWg0.en.vtt 404 B
Part 11-Module 01-Lesson 14_Validation/05. Where to use training vs. testing data 2-5v1jxDIwGqk.zh-CN.vtt 404 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ar.vtt 404 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.pt-BR.vtt 403 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.en.vtt 403 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-Q8hPJD_wXFY.zh-CN.vtt 403 B
Part 06-Module 01-Lesson 01_Working with MongoDB/30. Conclusion-mjPfjzOWiDw.zh-CN.vtt 403 B
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.ar.vtt 403 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.ja.vtt 403 B
Part 17-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.zh-CN.vtt 403 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.zh-CN.vtt 403 B
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.en.vtt 402 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/03. Assessing the Quality of Data Pt. 1-Dezhyk312lQ.zh-CN.vtt 402 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.ar.vtt 402 B
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.pt-BR.vtt 402 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.ar.vtt 402 B
Part 13-Module 01-Lesson 04_Design Principles/27. Alternatives to Rainbow Palettes-7ZvLztG6xhg.zh-CN.vtt 402 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.ar.vtt 402 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/16. Same Scores-VLgrNOLomc0.zh-CN.vtt 401 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/16. Same Scores-VLgrNOLomc0.zh-CN.vtt 401 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-80BAbiEWsaY.zh-CN.vtt 401 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.en.vtt 401 B
Part 03-Module 01-Lesson 20_L8 Estimation/29. Sampling Distributions-jJSkp9n3kA8.zh-CN.vtt 401 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.en.vtt 401 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-P-CGd_Vzpk0.zh-CN.vtt 401 B
Part 11-Module 01-Lesson 03_SVM/06. SVMs and Tricky Data Distributions-wbCq7wm81BU.zh-CN.vtt 401 B
Part 16-Module 02-Lesson 01_The Data Analysis Process/22. Drawing Conclusions-Glctk6ahdFU.zh-CN.vtt 401 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.pt-BR.vtt 401 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.en.vtt 400 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.pt-BR.vtt 400 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.en.vtt 400 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.zh-CN.vtt 400 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.pt-BR.vtt 399 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.pt-BR.vtt 399 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.en.vtt 399 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.en.vtt 399 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.en.vtt 399 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-hqO8kxRJdd4.zh-CN.vtt 399 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ar.vtt 399 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.en.vtt 399 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ar.vtt 399 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-hqO8kxRJdd4.zh-CN.vtt 399 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.en.vtt 399 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.en.vtt 398 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.en.vtt 398 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/17. Check You Out-tgni8KzxWzA.zh-CN.vtt 398 B
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.ja.vtt 398 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.ja.vtt 398 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.th.vtt 398 B
Part 03-Module 01-Lesson 13_L5 Standardizing/07. More Detail-XUrP62LvciA.zh-CN.vtt 397 B
Part 03-Module 01-Lesson 13_L5 Standardizing/15. Who's More Unpopular-SCy8YH5xu3Q.zh-CN.vtt 397 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.en.vtt 397 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-J0Ls7F-lN4o.en.vtt 397 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.ja.vtt 397 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.pt-BR.vtt 397 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.pt-BR.vtt 396 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-YY31Ggi4XyQ.zh-CN.vtt 396 B
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.pt-BR.vtt 396 B
Part 11-Module 01-Lesson 10_Feature Scaling/10. MinMax Rescaler Coding Quiz-xTEkF0voyoM.zh-CN.vtt 396 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.ar.vtt 396 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ar.vtt 396 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.pt-BR.vtt 396 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.ja.vtt 395 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.en.vtt 395 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ar.vtt 395 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.ja.vtt 395 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.es.vtt 394 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.en.vtt 394 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.en.vtt 394 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.en.vtt 394 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.en.vtt 394 B
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.pt-BR.vtt 393 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/19. Shoes - Decision-fgg81QJg89s.zh-CN.vtt 393 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.pt-BR.vtt 393 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.en-US.vtt 393 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.ar.vtt 393 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.es-ES.vtt 393 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.pt-BR.vtt 393 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.th.vtt 393 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.es.vtt 392 B
Part 07-Module 01-Lesson 01_GitHub Review/15. Starring interesting repositories-U3FUxkm1MxI.zh-CN.vtt 392 B
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.pt-BR.vtt 392 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.ja.vtt 392 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/25. Critical Region-skeY26k1hSs.zh-CN.vtt 391 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.ar.vtt 391 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.en.vtt 391 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.pt-BR.vtt 391 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/07. Significance-f0ZWCaOKW1Q.zh-CN.vtt 390 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.ja.vtt 390 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.es-ES.vtt 390 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.pt-BR.vtt 389 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-tX7p7HXlKBQ.zh-CN.vtt 389 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-GR1ZsrwhZUs.zh-CN.vtt 389 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.ja.vtt 389 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.pt-BR.vtt 389 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.pt-BR.vtt 389 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ja.vtt 389 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.ja.vtt 389 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.zh-CN.vtt 389 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.es-ES.vtt 389 B
Part 21-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.zh-CN.vtt 389 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-NtldeU_E4sI.zh-CN.vtt 388 B
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.ko.vtt 388 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/01. t-Distribution-TC2Ro6pFAqA.zh-CN.vtt 388 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.ar.vtt 388 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.es-ES.vtt 388 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.ar.vtt 387 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.pt-BR.vtt 387 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.en.vtt 387 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.ar.vtt 387 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.pt-BR.vtt 386 B
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.pt-BR.vtt 386 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/17. Alternative Hypothesis-Pk_BMZINZ0k.zh-CN.vtt 386 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d-smedG3-3mOE.zh-CN.vtt 386 B
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.en.vtt 386 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.pt-BR.vtt 386 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.pt-BR.vtt 386 B
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.pt-BR.vtt 386 B
Part 03-Module 01-Lesson 11_L4 Variability/36. Find Values-JP-mQPN9Sl4.zh-CN.vtt 385 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/16. Roll 2 Dice-D4bQbaCAUoE.zh-CN.vtt 385 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.pt-BR.vtt 385 B
Part 11-Module 01-Lesson 09_Clustering/03. How Many Clusters-8Ygq5dRV0Kk.zh-CN.vtt 385 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.ar.vtt 385 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.hr.vtt 384 B
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-kmVqaJ6n9Vk.zh-CN.vtt 383 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.pt-BR.vtt 383 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/23. Rent - t-Critical Values-WTmFRvH2AmI.zh-CN.vtt 383 B
Part 05-Module 01-Lesson 05_Data Quality/20. Conclusion-fSwaNltHTio.zh-CN.vtt 383 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.pt-BR.vtt 383 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.hr.vtt 383 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.pt-BR.vtt 383 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.pt-BR.vtt 382 B
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.pt-BR.vtt 382 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.en.vtt 382 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.it.vtt 382 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.en.vtt 382 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/10. Constructs-7umkXt9U5lE.zh-CN.vtt 381 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/10. Constructs-7umkXt9U5lE.zh-CN.vtt 381 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.pt-BR.vtt 381 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-WzwHLFlkxVA.zh-CN.vtt 380 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/27. t-Critical and Decision-k1plVVNoyeY.zh-CN.vtt 380 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.zh-CN.vtt 380 B
Part 17-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-7k5oAaZamCA.zh-CN.vtt 380 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-1GuHNqJNY2M.zh-CN.vtt 379 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.pt-BR.vtt 379 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.pt-BR.vtt 379 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-3NSPqjp6pFY.zh-CN.vtt 379 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-JSlSjQwhIAI.zh-CN.vtt 378 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-Za4LLPiE7pI.zh-CN.vtt 378 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.pt-BR.vtt 378 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/08. Filling in a Confusion Matrix-FwaYsmnlLM4.zh-CN.vtt 378 B
Part 14-Module 01-Lesson 02_Policy and Ethics for Experiments/15. Conclusion-PXBdIBgFTL4.zh-CN.vtt 378 B
Part 17-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.zh-CN.vtt 378 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.pt-BR.vtt 377 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.en.vtt 377 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.pt-BR.vtt 377 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.pt-BR.vtt 377 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.pt-BR.vtt 377 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.pt-BR.vtt 376 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.pt-BR.vtt 376 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-ObSZnD336CA.zh-CN.vtt 376 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.pt-BR.vtt 376 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.zh-CN.vtt 376 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.pt-BR.vtt 376 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.es.vtt 375 B
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.pt-BR.vtt 375 B
Part 03-Module 01-Lesson 20_L8 Estimation/02. Mean of Treated Population-jC4--44m3-I.zh-CN.vtt 375 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.pt-BR.vtt 375 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-4XEJJC-vSRw.zh-CN.vtt 375 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.pt-BR.vtt 375 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.it.vtt 375 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.pt-BR.vtt 375 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-YetpTU5SmUg.zh-CN.vtt 374 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.pt-BR.vtt 374 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.ja.vtt 374 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-X_5v9jxuLrQ.zh-CN.vtt 373 B
Part 09-Module 01-Lesson 03_Explore One Variable/29. Analyzing One Variable-yqwCYeaQAl0.zh-CN.vtt 373 B
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.ar.vtt 373 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.pt-BR.vtt 373 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.en.vtt 373 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.ja.vtt 373 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.pt-BR.vtt 373 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.es.vtt 372 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/27. Klout Parameters-CLGwm6tBHlk.zh-CN.vtt 372 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/34. Prone to Misinterpretations-DUVB_GCcado.zh-CN.vtt 372 B
Part 05-Module 01-Lesson 01_Data Extraction Fundamentals/08. Problematic Line-9bNGgRojUC0.zh-CN.vtt 372 B
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.ja.vtt 372 B
Part 11-Module 01-Lesson 07_Regressions/10. Equation of the Regression Line-O4jFvJWal6s.zh-CN.vtt 372 B
Part 11-Module 01-Lesson 07_Regressions/29. Problem with SSE-VD14oP-Ue6M.zh-CN.vtt 372 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.it.vtt 372 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/16. Integer SDs-CtbwhKXSEMs.zh-CN.vtt 371 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/38. Something Fun-S3UsHyKkoww.zh-CN.vtt 371 B
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.en.vtt 371 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.en.vtt 371 B
Part 11-Module 01-Lesson 04_Decision Trees/05. Constructing a Decision Tree 2nd Split-CIxvkVy1UBI.zh-CN.vtt 371 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.ja.vtt 371 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.en.vtt 370 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.pt-BR.vtt 370 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.ja.vtt 370 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.en.vtt 370 B
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.pt-BR.vtt 370 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/08. More than One Mode-9bsmO7cKzPk.zh-CN.vtt 369 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.es.vtt 369 B
Part 03-Module 01-Lesson 20_L8 Estimation/13. CI Range for Larger Sample Size-tl4mqs0SqX4.zh-CN.vtt 369 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.zh-CN.vtt 369 B
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.pt-BR.vtt 369 B
Part 11-Module 01-Lesson 10_Feature Scaling/05. Chris's Shirt Size by Our Metric-e83ZS4VqGZ0.zh-CN.vtt 369 B
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.ar.vtt 369 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-5Tbd3_a5Vug.zh-CN.vtt 369 B
Part 17-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.zh-CN.vtt 369 B
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.pt-BR.vtt 368 B
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.en.vtt 368 B
Part 03-Module 01-Lesson 13_L5 Standardizing/13. Katie - SDs Below-COHUHzCELK4.zh-CN.vtt 368 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.pt-BR.vtt 368 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.en.vtt 368 B
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.en.vtt 368 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.en.vtt 368 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.en.vtt 368 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.pt-BR.vtt 367 B
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.pt-BR.vtt 367 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.pt-BR.vtt 367 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.pt-BR.vtt 367 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.pt-BR.vtt 367 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/19. Which-Tailed Test-AXYl4jWsA3o.zh-CN.vtt 367 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/16. Mean Number of Shoes-DtdsK8K1OtI.pt-BR.vtt 367 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.zh-CN.vtt 367 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.ar.vtt 367 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.pt-BR.vtt 367 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.en.vtt 367 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.es-ES.vtt 367 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.en.vtt 366 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.en.vtt 366 B
Part 03-Module 01-Lesson 11_L4 Variability/18. Deviation from Mean-M43NnIroHws.zh-CN.vtt 366 B
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-OCLlqMAbxBM.zh-CN.vtt 366 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.pt-BR.vtt 366 B
Part 11-Module 01-Lesson 07_Regressions/13. Intercept Quiz-cuBxHYSPrkA.zh-CN.vtt 366 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-HAQ0-Skvzmc.zh-CN.vtt 366 B
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.en.vtt 366 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.en.vtt 366 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.es-ES.vtt 366 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-HAQ0-Skvzmc.zh-CN.vtt 366 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/34. Keyboards - SD of Differences-Ej8yntoeBw0.zh-CN.vtt 365 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.pt-BR.vtt 365 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-AeByX89sS4g.zh-CN.vtt 365 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.en.vtt 365 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.es.vtt 364 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.es.vtt 364 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/14. Average Karma Points per Post-p-ma7uqFNCM.zh-CN.vtt 364 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/08. The Demand of Diamonds-y8g6YeD7Gyk.zh-CN.vtt 364 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.en.vtt 364 B
Part 11-Module 01-Lesson 02_Naive Bayes/25. Prior and Posterior-45_uUhPcz38.zh-CN.vtt 364 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ar.vtt 364 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.en.vtt 364 B
Part 03-Module 01-Lesson 13_L5 Standardizing/18. Negative Z-Score-JdzOGxmq2jE.zh-CN.vtt 363 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.pt-BR.vtt 363 B
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.pt-BR.vtt 363 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.es.vtt 362 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.es.vtt 362 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.zh-CN.vtt 362 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.es.vtt 362 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.es.vtt 362 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/35. Draw Conclusions-yeHOhz4ZF1c.zh-CN.vtt 362 B
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.pt-BR.vtt 362 B
Part 05-Module 01-Lesson 03_Data in More Complex Formats/18. How Many Form Elements-GwzB76HYlFE.zh-CN.vtt 362 B
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.ar.vtt 362 B
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.en.vtt 362 B
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.pt-BR.vtt 362 B
Part 16-Module 02-Lesson 02_Data Analysis Process - Case Study 1/08. Troubleshooting With Appending-KwtjTmDMZGE.zh-CN.vtt 362 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.pt-BR.vtt 362 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.zh-CN.vtt 362 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.pt-BR.vtt 361 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.pt-BR.vtt 361 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-FY0DXe0lfrI.zh-CN.vtt 361 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality-s24-ikl3ZAs.zh-CN.vtt 361 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.en.vtt 360 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.en.vtt 360 B
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.ja.vtt 360 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.ar.vtt 360 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.pt-BR.vtt 360 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.es-ES.vtt 360 B
Part 03-Module 01-Lesson 11_L4 Variability/17. Calculate Mean-dXS9vjgXyg4.zh-CN.vtt 359 B
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.ar.vtt 359 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.ar.vtt 359 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.th.vtt 359 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.it.vtt 359 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.pt-BR.vtt 358 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.en.vtt 358 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.en.vtt 358 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.es-ES.vtt 358 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.en.vtt 358 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.en.vtt 357 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.pt-BR.vtt 357 B
Part 07-Module 01-Lesson 01_GitHub Review/05. Identify fixes for example “bad” profile-AF07y1oAim0.zh-CN.vtt 357 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.ar.vtt 357 B
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.ja.vtt 357 B
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.ja.vtt 357 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.ar.vtt 357 B
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.ar.vtt 357 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.ja.vtt 357 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.es-ES.vtt 357 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.en.vtt 357 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.es-ES.vtt 357 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.pt-BR.vtt 356 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.pt-BR.vtt 356 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.en.vtt 356 B
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.ar.vtt 356 B
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.ar.vtt 356 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-EDFp4wU5BMo.zh-CN.vtt 356 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.es-ES.vtt 356 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.pt-BR.vtt 356 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.en.vtt 355 B
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.pt-BR.vtt 355 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.ar.vtt 355 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.pt-BR.vtt 355 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-T7rdBFQQ0Fw.zh-CN.vtt 355 B
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.en.vtt 355 B
Part 11-Module 01-Lesson 09_Clustering/07. Match Points (again)-9J3IwQFXveI.zh-CN.vtt 355 B
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.pt-BR.vtt 355 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-JWl8lPGhlbY.zh-CN.vtt 355 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.es-ES.vtt 355 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.zh-CN.vtt 355 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.pt-BR.vtt 354 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.en.vtt 354 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.en.vtt 354 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.ar.vtt 354 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.pt-BR.vtt 354 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.th.vtt 354 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.pt-BR.vtt 354 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.en.vtt 354 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.pt-BR.vtt 354 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.pt-BR.vtt 353 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.pt-BR.vtt 353 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.en.vtt 353 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.en.vtt 353 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.pt-BR.vtt 353 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-potr9cTBlxI.zh-CN.vtt 353 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/23. Pooled Variance Sum of Squares-c0lWwW1Z9Ac.zh-CN.vtt 353 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.pt-BR.vtt 353 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.ja.vtt 353 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.en.vtt 353 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.en.vtt 352 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.pt-BR.vtt 352 B
Part 11-Module 01-Lesson 04_Decision Trees/27. Information Gain Calculation Part 6-zqmrW9N9WGw.zh-CN.vtt 352 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.ar.vtt 352 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/15. Classifying Chavez Correctly 2-HWW9BNHnPo0.zh-CN.vtt 352 B
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.ar.vtt 352 B
Part 17-Module 01-Lesson 16_Logistic Regression/19. Classifying Chavez Correctly 2-HWW9BNHnPo0.zh-CN.vtt 352 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.en.vtt 351 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.pt-BR.vtt 351 B
Part 04-Module 02-Lesson 02_NumPy and Pandas for 1D Data/06. Multiplying by a Scalar-jP1KfLaTtpU.zh-CN.vtt 351 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.en.vtt 351 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.ja.vtt 351 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.ja.vtt 351 B
Part 17-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.zh-CN.vtt 351 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.en.vtt 351 B
Part 21-Module 01-Lesson 06_Numpy Pandas - Part I/07. Multiplying by a Scalar-jP1KfLaTtpU.zh-CN.vtt 351 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/01. Compare Sample Means-l9Sy4qoLHVo.zh-CN.vtt 350 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.pt-BR.vtt 350 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.ja.vtt 350 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.en.vtt 350 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.es-ES.vtt 350 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.ja.vtt 350 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.en.vtt 350 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.es.vtt 349 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/18. Finches - Find t-Statistic-nBqsiW5r-98.zh-CN.vtt 349 B
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.pt-BR.vtt 349 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.en.vtt 349 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.en-US.vtt 349 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.pt-BR.vtt 349 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.en.vtt 349 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.en.vtt 349 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.en.vtt 348 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-Rw3QBEnIlJY.zh-CN.vtt 348 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.en.vtt 348 B
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.en.vtt 348 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.en.vtt 348 B
Part 17-Module 01-Lesson 04_Probability/12. Two Flips 5-G28YyiGFGWA.zh-CN.vtt 348 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.es-ES.vtt 348 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.es-ES.vtt 348 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.en.vtt 347 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.en.vtt 347 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.en.vtt 347 B
Part 03-Module 01-Lesson 11_L4 Variability/24. Formula for Avg. Abs. Dev.-_c780DW5Wuw.zh-CN.vtt 347 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.en.vtt 347 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.en.vtt 347 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.pt-BR.vtt 347 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.en.vtt 346 B
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.en.vtt 346 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.pt-BR.vtt 346 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.pt-BR.vtt 346 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.pt-BR.vtt 346 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.zh-CN.vtt 346 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.en.vtt 346 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.en.vtt 346 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.en.vtt 346 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.en.vtt 345 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.pt-BR.vtt 345 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-coHA_ziMiws.zh-CN.vtt 345 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/19. Linear Models in R-aUc0FKD4834.zh-CN.vtt 345 B
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.ja.vtt 345 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.ar.vtt 345 B
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.ar.vtt 345 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.ja.vtt 345 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.en.vtt 344 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.en.vtt 344 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.en.vtt 344 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.zh-CN.vtt 344 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.pt-BR.vtt 344 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.en.vtt 344 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.pt-BR.vtt 344 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.en.vtt 343 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.en.vtt 343 B
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.en.vtt 343 B
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.zh-CN.vtt 343 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.en.vtt 343 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.pt-BR.vtt 342 B
Part 11-Module 01-Lesson 13_PCA/20. Maximal Variance and Information Loss-DX_f02bUHT0.zh-CN.vtt 342 B
Part 13-Module 01-Lesson 05_Dimple.js/21. Two Identical Charts-maL-S68XvTc.pt-BR.vtt 342 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.th.vtt 342 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.en.vtt 342 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.ar.vtt 342 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.en.vtt 342 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.en.vtt 341 B
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.en.vtt 341 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-RQ_AHYQTSDA.zh-CN.vtt 341 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-edm9jPvzeAc.zh-CN.vtt 341 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.zh-CN.vtt 341 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.pt-BR.vtt 341 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.pt-BR.vtt 341 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.en.vtt 341 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.zh-CN.vtt 341 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.it.vtt 341 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ar.vtt 341 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.es.vtt 340 B
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.en.vtt 340 B
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.pt-BR.vtt 340 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.en.vtt 340 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.ar.vtt 340 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.pt-BR.vtt 340 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.pt-BR.vtt 340 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.en.vtt 340 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/31. Good Job!-ZZoeeLpWcmU.zh-CN.vtt 339 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.en.vtt 339 B
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.ja.vtt 339 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/05. Frances Gerety-n9heeZ1Dw8A.en.vtt 339 B
Part 11-Module 01-Lesson 02_Naive Bayes/26. Normalizing 1-aALYYSwS7MM.zh-CN.vtt 339 B
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.ar.vtt 339 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.en.vtt 339 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ar.vtt 339 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.pt-BR.vtt 339 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.th.vtt 339 B
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.pt-BR.vtt 338 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-47JDwoDUxP8.zh-CN.vtt 338 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.en.vtt 338 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.it.vtt 338 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.es.vtt 337 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.es.vtt 337 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.pt-BR.vtt 337 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/29. Rent - Margin of Error-nHF7LgYaZnE.zh-CN.vtt 337 B
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.en.vtt 337 B
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.ar.vtt 337 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.en.vtt 337 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.pt-BR.vtt 337 B
Part 17-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.es-ES.vtt 337 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.en.vtt 337 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.pt-BR.vtt 337 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.zh-CN.vtt 336 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/09. t-Critical Values-e2C4tEKNtqs.zh-CN.vtt 336 B
Part 09-Module 01-Lesson 03_Explore One Variable/20. The Spread of Memes-B-khnSU3DfM.zh-CN.vtt 336 B
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.ja.vtt 336 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.ar.vtt 336 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.en.vtt 336 B
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.en.vtt 335 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.pt-BR.vtt 335 B
Part 11-Module 01-Lesson 10_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-l6YXxmCNtHk.zh-CN.vtt 335 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.zh-CN.vtt 335 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.pt-BR.vtt 335 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.zh-CN.vtt 335 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.es.vtt 334 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.en.vtt 334 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.en.vtt 334 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-22SXauLJVd4.zh-CN.vtt 334 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.ja.vtt 334 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ar.vtt 334 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.en.vtt 333 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.pt-BR.vtt 333 B
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.pt-BR.vtt 333 B
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.en.vtt 333 B
Part 03-Module 01-Lesson 20_L8 Estimation/30. Z-Scores of Sample Means-AM-d6qA5nnI.zh-CN.vtt 333 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.en.vtt 333 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.en.vtt 333 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/17. Powell Precision and Recall-QWWq77k-K_0.zh-CN.vtt 333 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.en.vtt 333 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.es-ES.vtt 333 B
Part 17-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-QWWq77k-K_0.zh-CN.vtt 333 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.en.vtt 332 B
Part 09-Module 01-Lesson 05_Explore Two Variables/21. A New Perspective-bUvlDsmmpIo.zh-CN.vtt 332 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price--P5lMGuVA6U.en.vtt 332 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.en.vtt 332 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.zh-CN.vtt 332 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.es-ES.vtt 332 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.ja.vtt 332 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.pt-BR.vtt 332 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/10. Continents-LHLgEooUT4E.zh-CN.vtt 331 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.en.vtt 331 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-kW_p0VHNEPM.pt-BR.vtt 331 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-9-yTPJl_DIw.zh-CN.vtt 331 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/11. Overplotting Revisited-AvokBc1DoEU.zh-CN.vtt 331 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.en.vtt 331 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.en.vtt 331 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.pt-BR.vtt 331 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.pt-BR.vtt 331 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.ja.vtt 331 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.zh-CN.vtt 331 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-C8I9uVBKems.pt-BR.vtt 330 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.en.vtt 329 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-68_OkDcn6dI.zh-CN.vtt 329 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.ja.vtt 329 B
Part 14-Module 01-Lesson 03_Choosing and Characterizing Metrics/04. High Level Metrics Customer Funnel-yg5c1caIB4E.zh-CN.vtt 329 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.es-ES.vtt 329 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.pt-BR.vtt 329 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-5DZTwMn7GAY.zh-CN.vtt 328 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.pt-BR.vtt 328 B
Part 11-Module 01-Lesson 07_Regressions/16. Handoff to Katie-M3Nwl_B_bZ8.zh-CN.vtt 328 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.en-US.vtt 327 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.en.vtt 327 B
Part 05-Module 02-Lesson 05_Deeper into SQL/13. Trying Out DB API-QTq9pGMoZAE.zh-CN.vtt 327 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-vhDpWgdpSHg.zh-CN.vtt 327 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.ar.vtt 327 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.es-ES.vtt 327 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.ja.vtt 327 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.es.vtt 326 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-ZU9uRiqLgxA.zh-CN.vtt 326 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.pt-BR.vtt 326 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.pt-BR.vtt 326 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.ar.vtt 326 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.ja.vtt 326 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-hXyXlk0gYzk.ja.vtt 326 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.ar.vtt 326 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.ja.vtt 325 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.en.vtt 325 B
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.en.vtt 325 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-U3ZnXlDS5No.zh-CN.vtt 325 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.en.vtt 325 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.ar.vtt 325 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.zh-CN.vtt 325 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.pt-BR.vtt 324 B
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.en.vtt 324 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.pt-BR.vtt 324 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.pt-BR.vtt 324 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.it.vtt 324 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.en.vtt 323 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/15. Treatment-zWmH6ajoLtE.zh-CN.vtt 323 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/12. Acne Medication t-Statistic-LDdm06-FHYI.zh-CN.vtt 323 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.ar.vtt 323 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.zh-CN.vtt 323 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.ja.vtt 323 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.es.vtt 322 B
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.es.vtt 322 B
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.pt-BR.vtt 322 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.en.vtt 322 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.en.vtt 322 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.zh-CN.vtt 321 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/31. Controlled Factors-2ijmV_oIGHo.zh-CN.vtt 321 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.es.vtt 321 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.en.vtt 321 B
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.pt-BR.vtt 321 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.en.vtt 321 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.en.vtt 321 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.en-US.vtt 321 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.en.vtt 320 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.pt-BR.vtt 320 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.en.vtt 320 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.en.vtt 320 B
Part 17-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability-V_Gqm42WodI.zh-CN.vtt 320 B
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.en.vtt 320 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.en.vtt 319 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.en.vtt 319 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.pt-BR.vtt 319 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/09. Connecting Demand and Price Distribution-Rj6g9jpX9MQ.zh-CN.vtt 319 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-M2Sp-Y2a71c.zh-CN.vtt 319 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/07. Confusion Matrix Practice 2-XN1eS7boCNg.en.vtt 319 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.ar.vtt 319 B
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.ar.vtt 319 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.hr.vtt 319 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ar.vtt 319 B
Part 17-Module 01-Lesson 16_Logistic Regression/12. Confusion Matrix Practice 2-XN1eS7boCNg.en.vtt 319 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.ar.vtt 319 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.zh-CN.vtt 318 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/11. Operational Definitions-1Wajquw8I10.zh-CN.vtt 318 B
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.pt-BR.vtt 318 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.en.vtt 318 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.es-ES.vtt 318 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/07. Proportion from Countries-gww_oBZTf5k.zh-CN.vtt 317 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-MPPgcjHAfkA.zh-CN.vtt 317 B
Part 03-Module 01-Lesson 05_PS 2a Visualizing Data/01. 1. Blood Types-qhhrjvLF8H8.zh-CN.vtt 317 B
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.ar.vtt 317 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.pt-BR.vtt 317 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.en.vtt 317 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.pt-BR.vtt 317 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.es.vtt 316 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.en.vtt 316 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.ja.vtt 316 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.en.vtt 316 B
Part 11-Module 01-Lesson 13_PCA/04. Slightly Less Perfect Data-g5yfjKWIKN4.zh-CN.vtt 316 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-9frwavCQvGg.zh-CN.vtt 316 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LconwqN7hJs.zh-CN.vtt 316 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.en.vtt 315 B
Part 11-Module 01-Lesson 08_Outliers/06. Effect of Outlier Removal on Regression-iEvYp4hL6OY.zh-CN.vtt 315 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.en.vtt 315 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.it.vtt 315 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.ja.vtt 315 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ar.vtt 315 B
Part 03-Module 01-Lesson 11_L4 Variability/06. Mark Z the Outlier-_UyoOnmH1X8.zh-CN.vtt 314 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.ja.vtt 314 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.ja.vtt 314 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.pt-BR.vtt 314 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.it.vtt 314 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.zh-CN.vtt 314 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.en.vtt 313 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/07. Design Code Tell-b1V_L3qFIUk.zh-CN.vtt 313 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.en.vtt 313 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.en.vtt 313 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.pt-BR.vtt 312 B
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.pt-BR.vtt 312 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-KaBa9N2TdnQ.zh-CN.vtt 312 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.zh-CN.vtt 312 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-Bp6oBbLw8qE.zh-CN.vtt 312 B
Part 11-Module 01-Lesson 09_Clustering/06. Moving Centers 2-uC1Xwc7warg.en.vtt 312 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ar.vtt 312 B
Part 17-Module 01-Lesson 04_Probability/14. One Head 2-JHx3ucNS9f4.hr.vtt 312 B
Part 11-Module 01-Lesson 02_Naive Bayes/14. A Good Linear Decision Surface-sudTOiG-NJo.zh-CN.vtt 311 B
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.pt-BR.vtt 311 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.it.vtt 311 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.en.vtt 310 B
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.en.vtt 310 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/02. Everyday Meaning-DKxww0fCCAA.zh-CN.vtt 310 B
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.en.vtt 310 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.en.vtt 310 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-tiv8VKPL7jg.ja.vtt 310 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.en.vtt 309 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.en.vtt 309 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.es.vtt 309 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.en.vtt 309 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.ar.vtt 309 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.pt-BR.vtt 309 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.zh-CN.vtt 309 B
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.pt-BR.vtt 309 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.zh-CN.vtt 308 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/34. Katie's Hand-i87r_q2SrLI.zh-CN.vtt 308 B
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.en.vtt 308 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-6RNfHbEL4ZQ.zh-CN.vtt 308 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-AP3YFEoi8_M.zh-CN.vtt 308 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/16. Null Hypothesis-KFSiwhv4q7s.zh-CN.vtt 308 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.ar.vtt 308 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.zh-CN.vtt 308 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.it.vtt 308 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.en.vtt 307 B
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.pt-BR.vtt 307 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.pt-BR.vtt 307 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.it.vtt 307 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.en.vtt 307 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.zh-CN.vtt 307 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.pt-BR.vtt 307 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/13. Iterative Procedure-r2s9INGd-Ls.zh-CN.vtt 306 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/13. Price vs. Carat and Clarity-g88Q5qyiZxE.zh-CN.vtt 306 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.pt-BR.vtt 306 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.ar.vtt 306 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.en.vtt 306 B
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.pt-BR.vtt 306 B
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.pt-BR.vtt 306 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.en.vtt 306 B
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.en.vtt 305 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.en.vtt 305 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-Adzhg-M3Pvk.en.vtt 305 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-AjI84ujXBHk.pt-BR.vtt 305 B
Part 11-Module 01-Lesson 13_PCA/05. Trickiest Data Dimensionality-vIxDt0bNV9g.zh-CN.vtt 305 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.pt-BR.vtt 305 B
Part 13-Module 01-Lesson 05_Dimple.js/26. Bar Chart The Good-oTAhEKrWq2g.zh-CN.vtt 305 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.ja.vtt 305 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.hr.vtt 305 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.ja.vtt 305 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.th.vtt 305 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.zh-CN.vtt 305 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.pt-BR.vtt 305 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.pt-BR.vtt 304 B
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-xE3Rgjv2Vww.zh-CN.vtt 304 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.pt-BR.vtt 304 B
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.en.vtt 304 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/04. Critical Values 0.01-9EFRrU4WBs4.zh-CN.vtt 304 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/04. DF - Choose n Numbers-_Ns0gk4T7eo.zh-CN.vtt 304 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/21. Shoes - Calculate CI-S8sB8ph_bQM.zh-CN.vtt 304 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.ar.vtt 304 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.ja.vtt 304 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.zh-CN.vtt 304 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-z_eElEkVOPY.ja.vtt 304 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-6pxpT3bZI54.zh-CN.vtt 303 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/25. Order Measures of Center 2-m2waMNsE1sU.es.vtt 303 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.pt-BR.vtt 303 B
Part 11-Module 01-Lesson 11_Text Learning/08. Stopwords-2FQu07aKLwg.zh-CN.vtt 303 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ar.vtt 303 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ar.vtt 303 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-udduksMWMB4.zh-CN.vtt 303 B
Part 17-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.zh-CN.vtt 303 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/11. Find the Mean-El5cY2jlzuM.zh-CN.vtt 302 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/17. What Can You Expect-2wHoLFHnPZs.zh-CN.vtt 302 B
Part 03-Module 01-Lesson 13_L5 Standardizing/09. Continuous Distribution-IncW1Q44jMk.zh-CN.vtt 302 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/19. Between 10 and 16-lMm_BrpheLM.zh-CN.vtt 302 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/26. Increase Sample Size-_Oh9-SQDtYg.zh-CN.vtt 302 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.en.vtt 302 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-P4tyKSWJUZc.zh-CN.vtt 302 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.ar.vtt 302 B
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.ar.vtt 302 B
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.pt-BR.vtt 302 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.en.vtt 302 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ar.vtt 302 B
Part 17-Module 01-Lesson 05_Binomial Distribution/01. Binomial-x1yamZeOMPY.zh-CN.vtt 302 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ar.vtt 302 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.ja.vtt 302 B
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.en.vtt 302 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/22. Continent Graph-RnUTCqsJD68.zh-CN.vtt 301 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.en.vtt 301 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.ar.vtt 301 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.ja.vtt 301 B
Part 17-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-RBfFHxEjsIU.ja.vtt 301 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.es-ES.vtt 301 B
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-baWB4xYNMIs.zh-CN.vtt 300 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.pt-BR.vtt 300 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-a5RRRMRZl8I.zh-CN.vtt 300 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-iyX0-eXStbw.ja.vtt 300 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.ja.vtt 300 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.ar.vtt 299 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.pt-BR.vtt 299 B
Part 11-Module 01-Lesson 13_PCA/18. Maximal Variance-FpQm_dYA9LM.zh-CN.vtt 299 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.en.vtt 299 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.th.vtt 299 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-LCrrPfsXaVc.zh-CN.vtt 298 B
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.en.vtt 298 B
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.en.vtt 298 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.pt-BR.vtt 298 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/03. Meal Prices-f_WdPsfeLDs.zh-CN.vtt 298 B
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.ar.vtt 298 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.en.vtt 298 B
Part 17-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-CQHRYIU6v9Q.ja.vtt 298 B
Part 17-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-41HCYR-NW-w.zh-CN.vtt 298 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.en.vtt 297 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.en.vtt 297 B
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.ja.vtt 297 B
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.pt-BR.vtt 297 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.ja.vtt 297 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.ja.vtt 297 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.zh-CN.vtt 297 B
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-4VKOJowrOoU.pt-BR.vtt 296 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.en.vtt 296 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.ja.vtt 296 B
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.ar.vtt 296 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-8jcCGD986jk.zh-CN.vtt 296 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.ja.vtt 296 B
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.en.vtt 295 B
Part 11-Module 01-Lesson 02_Naive Bayes/05. Features Visualization Quiz-aMOZWZO5hZ8.zh-CN.vtt 295 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/18. Better Sample-I487nBkmUoM.zh-CN.vtt 294 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/18. Better Sample-I487nBkmUoM.zh-CN.vtt 294 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.es.vtt 294 B
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.pt-BR.vtt 294 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.pt-BR.vtt 294 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-GCk9hNs1uxY.pt-BR.vtt 294 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-CMIM_Ocu8vg.zh-CN.vtt 294 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-CMIM_Ocu8vg.zh-CN.vtt 294 B
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.pt-BR.vtt 293 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.en.vtt 293 B
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.en.vtt 293 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.pt-BR.vtt 293 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.ja.vtt 293 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-YkaVgZ-yFrM.zh-CN.vtt 293 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.pt-BR.vtt 293 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.pt-BR.vtt 292 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.pt-BR.vtt 292 B
Part 03-Module 01-Lesson 20_L8 Estimation/03. Population Mean vs. Sample Mean-dsje3j3gn_s.zh-CN.vtt 292 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-vG3ahYyLHlQ.zh-CN.vtt 292 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.en.vtt 292 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.pt-BR.vtt 292 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.en.vtt 292 B
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.en.vtt 292 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.en.vtt 292 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/24. Biased Graphs-VkZ-W3kh9PA.zh-CN.vtt 291 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.en.vtt 291 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.pt-BR.vtt 291 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/15. Finches-Y6qz1XqyO9w.zh-CN.vtt 291 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-C8I9uVBKems.en.vtt 291 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.en.vtt 291 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.ja.vtt 291 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.pt-BR.vtt 291 B
Part 11-Module 01-Lesson 07_Regressions/12. Slope Quiz-wnIQ6fCVD40.zh-CN.vtt 291 B
Part 11-Module 01-Lesson 07_Regressions/15. Adding An Intercept-xPDk70gKkjk.zh-CN.vtt 291 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.ar.vtt 291 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.zh-CN.vtt 291 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.hr.vtt 291 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.it.vtt 291 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.pt-BR.vtt 291 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-C3Fqiu6HJog.zh-CN.vtt 291 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.es.vtt 290 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.pt-BR.vtt 290 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-3rL-Vk-QIB8.zh-CN.vtt 290 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.en.vtt 290 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.en.vtt 290 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split--3VPMBIwTtE.pt-BR.vtt 289 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.en.vtt 289 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.ar.vtt 289 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.hr.vtt 289 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.it.vtt 289 B
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.en.vtt 288 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/19. Null Hypothesis-ldiOcCeZvx4.zh-CN.vtt 288 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/24. Equation for Recall-2cUiqlbt-hc.zh-CN.vtt 288 B
Part 13-Module 01-Lesson 04_Design Principles/17. Pre-attentive Processing-ZmDbDYoRxwQ.zh-CN.vtt 288 B
Part 17-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.zh-CN.vtt 288 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.pt-BR.vtt 287 B
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.pt-BR.vtt 287 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/20. Standard Error When n Increases-mbCavcKeZqo.zh-CN.vtt 287 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.pt-BR.vtt 287 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.pt-BR.vtt 287 B
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.en.vtt 287 B
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.zh-CN.vtt 287 B
Part 11-Module 01-Lesson 14_Validation/07. Where to use training vs. testing data 4-3RuKO3PQWg0.zh-CN.vtt 287 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/09. What We Need to Compare the Means-SAjAfP-Y9O8.zh-CN.vtt 286 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.ko.vtt 286 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-_h2C0TCvXvA.zh-CN.vtt 286 B
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.en.vtt 286 B
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.zh-CN.vtt 286 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ar.vtt 286 B
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-OBxWYhF4VdI.zh-CN.vtt 285 B
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.pt-BR.vtt 285 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.ja.vtt 285 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.zh-CN.vtt 285 B
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.en.vtt 285 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.en.vtt 285 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.ar.vtt 285 B
Part 13-Module 01-Lesson 08_Animation and Interaction/06. GeoJSON vs Shapefile-QeTWVPi1Evo.zh-CN.vtt 285 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.pt-BR.vtt 285 B
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.ar.vtt 284 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.pt-BR.vtt 284 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-7iOMOs56gZE.zh-CN.vtt 283 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.ja.vtt 283 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.ar.vtt 283 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/05. Confusion Matrices-bEAaNv-CBQ4.zh-CN.vtt 283 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ar.vtt 283 B
Part 17-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.zh-CN.vtt 283 B
Part 03-Module 01-Lesson 06_PS 2b Additional Practice (Optional)/01. 7. Ode to n-c2Das5kJFe4.zh-CN.vtt 282 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/19. Standard Error for Avg of 5 Dice-18DMT9dnLPE.zh-CN.vtt 282 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.pt-BR.vtt 282 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.en.vtt 282 B
Part 11-Module 01-Lesson 03_SVM/09. Handoff to Katie-GkqOdgZnkig.zh-CN.vtt 282 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.ar.vtt 282 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.ar.vtt 282 B
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.en.vtt 282 B
Part 17-Module 01-Lesson 07_Bayes Rule/23. Robot Sensing 3--6l4_oprDOk.zh-CN.vtt 282 B
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.pt-BR.vtt 281 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.ar.vtt 281 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.ar.vtt 281 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.ja.vtt 281 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.pt-BR.vtt 281 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.en.vtt 281 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.es-ES.vtt 281 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.pt-BR.vtt 281 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/01. Likely or Unlikely-9jGIDxEr9A4.zh-CN.vtt 280 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.pt-BR.vtt 280 B
Part 13-Module 01-Lesson 05_Dimple.js/32. Adding a Title Using D3-0E08XPKeRNg.zh-CN.vtt 280 B
Part 17-Module 01-Lesson 04_Probability/15. One Of Three 1-rxfHfjy9Mm4.zh-CN.vtt 280 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.pt-BR.vtt 279 B
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.pt-BR.vtt 279 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-Qlg5L4TWcZs.zh-CN.vtt 279 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.pt-BR.vtt 279 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.ja.vtt 279 B
Part 11-Module 01-Lesson 11_Text Learning/04. Mr. Day Loves a Nice Day-uETh8McUAfY.pt-BR.vtt 279 B
Part 13-Module 01-Lesson 01_Visualization Fundamentals/27. D3 Web Technologies-LoLj_Ecohew.zh-CN.vtt 279 B
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.en.vtt 279 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.ar.vtt 279 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.en.vtt 279 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.pt-BR.vtt 278 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.ar.vtt 278 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.ar.vtt 278 B
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.ja.vtt 277 B
Part 11-Module 01-Lesson 09_Clustering/14. Limitations of K-Means-nvLhUSSUhiY.zh-CN.vtt 277 B
Part 11-Module 01-Lesson 13_PCA/03. One-Dimensional, or Two-QsncWsyboFk.zh-CN.vtt 277 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.en.vtt 277 B
Part 17-Module 01-Lesson 06_Conditional Probability/05. Medical Example 4-pL8Bf6tck_A.zh-CN.vtt 277 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.en.vtt 277 B
Part 18-Module 03-Lesson 01_Assessing Data/11. Quality Visual Assessment 2 -dRbjnKOnd0Y.zh-CN.vtt 277 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/24. Z-Score of Sample Mean-Hj2HADsZ-rM.zh-CN.vtt 276 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.pt-BR.vtt 276 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.pt-BR.vtt 276 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.pt-BR.vtt 276 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/05. Mode of Distribution-s9dHF4MMGx0.zh-CN.vtt 275 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-k7eajev401c.pt-BR.vtt 275 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-ys9w-NNKCcU.zh-CN.vtt 275 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.pt-BR.vtt 274 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.ar.vtt 274 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.pt-BR.vtt 273 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/32. Compute CI-Adzhg-M3Pvk.zh-CN.vtt 273 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.ar.vtt 273 B
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.en.vtt 273 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-V0FNwMKhIVM.pt-BR.vtt 273 B
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.en.vtt 273 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.pt-BR.vtt 273 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/33. What Happened-6mxt0l8IpOM.zh-CN.vtt 272 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/17. Finches - Mean and s-nInJKeAmAeY.zh-CN.vtt 272 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.pt-BR.vtt 272 B
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.pt-BR.vtt 272 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.es-ES.vtt 272 B
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-E1iDHrumLoo.zh-CN.vtt 271 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.ar.vtt 271 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.zh-CN.vtt 271 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.pt-BR.vtt 271 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.pt-BR.vtt 270 B
Part 13-Module 01-Lesson 04_Design Principles/37. Chartjunk Qualities-R6Sggtsz5LM.zh-CN.vtt 270 B
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.pt-BR.vtt 269 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.pt-BR.vtt 269 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/06. Meal Price SEM-jHzmtwd-xTs.zh-CN.vtt 269 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.pt-BR.vtt 269 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-m9IQqYf6ThU.zh-CN.vtt 268 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.pt-BR.vtt 268 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-evwkqnO9BHY.zh-CN.vtt 268 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.zh-CN.vtt 268 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.en.vtt 268 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.es.vtt 267 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.en.vtt 267 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/17. Less than 5-CHHhDWRG49A.zh-CN.vtt 267 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.th.vtt 267 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.zh-CN.vtt 266 B
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.pt-BR.vtt 266 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.ar.vtt 266 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.pt-BR.vtt 265 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/27. Rent - CI-C8I9uVBKems.zh-CN.vtt 265 B
Part 11-Module 01-Lesson 02_Naive Bayes/12. From Scatterplots to Predictions 2-tkllhaHoko8.en.vtt 265 B
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.ar.vtt 265 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.ar.vtt 265 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.ar.vtt 265 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ar.vtt 265 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.pt-BR.vtt 265 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ar.vtt 265 B
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.ar.vtt 265 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.pt-BR.vtt 264 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.pt-BR.vtt 264 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.zh-CN.vtt 264 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.zh-CN.vtt 264 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.pt-BR.vtt 264 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.ja.vtt 264 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.pt-BR.vtt 264 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.ja.vtt 263 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.ar.vtt 263 B
Part 11-Module 01-Lesson 04_Decision Trees/06. Class Labels After Second Split-A7KKnDmZBA0.zh-CN.vtt 263 B
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.en.vtt 263 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.en.vtt 263 B
Part 11-Module 01-Lesson 11_Text Learning/13. Weighting by Term Frequency-pt_S3HwE5GY.zh-CN.vtt 263 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-KmEfiWATLUI.zh-CN.vtt 262 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/17. Shoes - Standard Error-sYOGafbS30Q.zh-CN.vtt 262 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.ar.vtt 262 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.en.vtt 262 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.ja.vtt 262 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.pt-BR.vtt 262 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.es.vtt 261 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.en.vtt 261 B
Part 03-Module 01-Lesson 20_L8 Estimation/12. Generalize CI-HgumODgJSdQ.zh-CN.vtt 261 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/23. Critical Values 0.05-KQZnIM7YWAg.zh-CN.vtt 261 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.pt-BR.vtt 261 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.ja.vtt 261 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.pt-BR.vtt 261 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.ja.vtt 261 B
Part 03-Module 01-Lesson 20_L8 Estimation/14. CI When n = 250-mCp7zkPv6o4.zh-CN.vtt 260 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-yu70KwoztEg.zh-CN.vtt 260 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/13. Acne Medication - t-Critical Values-CRlOfleyRNY.zh-CN.vtt 260 B
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.zh-CN.vtt 260 B
Part 11-Module 01-Lesson 04_Decision Trees/19. Entropy Calculation Part 4-bhwb2v9rEdI.en.vtt 260 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.en.vtt 260 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.pt-BR.vtt 260 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-jPspIs-fNxg.ja.vtt 260 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.es-ES.vtt 260 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.en.vtt 259 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.zh-CN.vtt 259 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-c7UjSq7Fmr8.zh-CN.vtt 259 B
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.en.vtt 258 B
Part 03-Module 01-Lesson 13_L5 Standardizing/23. Convert to Z-Score-tBlCLuL2tFc.zh-CN.vtt 258 B
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.ar.vtt 258 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.es-ES.vtt 258 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.en.vtt 257 B
Part 17-Module 01-Lesson 03_Admissions Case Study/06. Gender Bias-DeWp0hnRq4g.zh-CN.vtt 257 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.es-ES.vtt 257 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.en.vtt 256 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.en.vtt 256 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.ja.vtt 256 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.ar.vtt 256 B
Part 11-Module 01-Lesson 03_SVM/05. Practice with Margins-l3zXhTxQiTs.zh-CN.vtt 256 B
Part 11-Module 01-Lesson 04_Decision Trees/07. Constructing A Decision TreeThird Split-RxySNoOmXnc.ja.vtt 256 B
Part 11-Module 01-Lesson 04_Decision Trees/12. Decision Tree Accuracy-1z5mVNdF1KA.pt-BR.vtt 256 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.en.vtt 256 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-obhHCeHpysw.zh-CN.vtt 256 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.en.vtt 256 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.en.vtt 256 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-obhHCeHpysw.zh-CN.vtt 256 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/16. Smaller Bin-U74HWk-E_jg.zh-CN.vtt 255 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.ja.vtt 255 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-4YP0K-5c310.pt-BR.vtt 255 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.zh-CN.vtt 255 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-DzyOcsBIncA.zh-CN.vtt 255 B
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200--scGDVG9KJ8.zh-CN.vtt 254 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.pt-BR.vtt 254 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.ja.vtt 254 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.en.vtt 254 B
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.pt-BR.vtt 254 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ar.vtt 254 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-4LVRNqpdxsw.ja.vtt 254 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.pt-BR.vtt 254 B
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.pt-BR.vtt 253 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.pt-BR.vtt 253 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.en.vtt 253 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.pt-BR.vtt 253 B
Part 11-Module 01-Lesson 04_Decision Trees/23. Information Gain Calculation Part 2-t4qaavAslSw.zh-CN.vtt 253 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.pt-BR.vtt 253 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/25. Results of Hypothesis Test--Ecdsb39FnM.en.vtt 252 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.en.vtt 252 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/04. Average Meal Price-mlNMENDGqtk.zh-CN.vtt 252 B
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.en.vtt 252 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.en.vtt 252 B
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.en.vtt 252 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.hr.vtt 252 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.th.vtt 252 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.es-ES.vtt 252 B
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ar.vtt 252 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.en.vtt 252 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.en.vtt 251 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.en.vtt 251 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.pt-BR.vtt 251 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.pt-BR.vtt 251 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.ja.vtt 251 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.ja.vtt 251 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.ar.vtt 251 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/13. How Many Schroeder Predictions-r8stm2et_hI.zh-CN.vtt 251 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.es-ES.vtt 251 B
Part 17-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.zh-CN.vtt 251 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-n7II63ei3LU.zh-CN.vtt 250 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.en.vtt 250 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.pt-BR.vtt 250 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.en.vtt 250 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.ar.vtt 250 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ar.vtt 250 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.zh-CN.vtt 250 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.pt-BR.vtt 249 B
Part 11-Module 01-Lesson 02_Naive Bayes/34. Bayesian Probabilities On Your Own-2StCBxTOoK0.zh-CN.vtt 249 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.pt-BR.vtt 249 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.pt-BR.vtt 249 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.pt-BR.vtt 249 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.pt-BR.vtt 249 B
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.en.vtt 248 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.pt-BR.vtt 248 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/04. Price and Carat Relationship-gG4xwgj1yVA.zh-CN.vtt 248 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.pt-BR.vtt 248 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.pt-BR.vtt 248 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.ar.vtt 248 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-D27UwulJc2c.zh-CN.vtt 248 B
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.zh-CN.vtt 248 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.zh-CN.vtt 248 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.it.vtt 248 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.ja.vtt 248 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.en.vtt 248 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.ar.vtt 248 B
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.pt-BR.vtt 247 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-SJ9JldQSF5w.pt-BR.vtt 247 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/26. t-Statistic-KvaW3rL7u4k.zh-CN.vtt 247 B
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.en.vtt 247 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.pt-BR.vtt 247 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.pt-BR.vtt 247 B
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.pt-BR.vtt 247 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-P4uljJ_OP6I.ja.vtt 247 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.en.vtt 247 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.ja.vtt 247 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.es.vtt 246 B
Part 03-Module 01-Lesson 11_L4 Variability/25. Squared Deviations-oA37LlWNYCw.zh-CN.vtt 246 B
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.en.vtt 246 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.en.vtt 246 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.zh-CN.vtt 246 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.ja.vtt 246 B
Part 11-Module 01-Lesson 11_Text Learning/03. A Very Nice Day-yB866_TLZB8.en.vtt 246 B
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.en.vtt 246 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.en.vtt 246 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.pt-BR.vtt 246 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.pt-BR.vtt 245 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.en.vtt 245 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/30. Rent - Increase n-Z3Fl0WPJFoA.zh-CN.vtt 245 B
Part 11-Module 01-Lesson 13_PCA/07. Center of a New Coordinate System-1ask5zHGQKM.zh-CN.vtt 245 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.en.vtt 245 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-aE-ZZw8QVWo.zh-CN.vtt 244 B
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.ar.vtt 244 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-s_-I8mbrfw0.zh-CN.vtt 244 B
Part 14-Module 01-Lesson 05_Analyzing Results/05. Checking Invariants-NixhPePGk-s.zh-CN.vtt 244 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.en.vtt 244 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.zh-CN.vtt 244 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.th.vtt 244 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.pt-BR.vtt 243 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.pt-BR.vtt 243 B
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.ja.vtt 243 B
Part 11-Module 01-Lesson 13_PCA/24. Maximum Number of PCs Quiz-oOUx6NHppdQ.zh-CN.vtt 243 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.ja.vtt 243 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.es-ES.vtt 243 B
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.en.vtt 242 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.es-ES.vtt 242 B
Part 03-Module 01-Lesson 13_L5 Standardizing/20. SD of Standardized Distribution-0JZyJ5_T858.zh-CN.vtt 241 B
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.zh-CN.vtt 241 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-uZk43roQbt0.en.vtt 241 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.en.vtt 241 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.pt-BR.vtt 241 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.ar.vtt 241 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/19. True Positives in Eigenfaces-TWGqylKdGWs.zh-CN.vtt 241 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-FQM7i07EqGo.zh-CN.vtt 241 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.en.vtt 241 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.ja.vtt 241 B
Part 17-Module 01-Lesson 16_Logistic Regression/23. True Positives in Eigenfaces-TWGqylKdGWs.zh-CN.vtt 241 B
How you can help Team-FTU.txt 241 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-h9IP6OuMQrk.zh-CN.vtt 240 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/04. Total Number of Samples-s0J73PTr9Rw.zh-CN.vtt 240 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.hi.vtt 240 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.en.vtt 240 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.en.vtt 240 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.en.vtt 240 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.en.vtt 240 B
Part 11-Module 01-Lesson 06_Datasets and Questions/06. Types of Data Quiz 2-k63Why0c1KU.pt-BR.vtt 240 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -5GuI-r2Dj1Y.en-US.vtt 240 B
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.pt-BR.vtt 240 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.en.vtt 240 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.it.vtt 240 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.th.vtt 240 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.th.vtt 240 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.pt-BR.vtt 240 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.en.vtt 239 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/31. Margin of Error-cLyzI4feDEw.zh-CN.vtt 239 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.pt-BR.vtt 239 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.en.vtt 239 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.it.vtt 239 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-vLhdJtXx060.es-ES.vtt 239 B
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.en.vtt 238 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.pt-BR.vtt 238 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-DS_4EiegbtQ.pt-BR.vtt 238 B
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.ar.vtt 238 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.en.vtt 238 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.hr.vtt 238 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.en.vtt 238 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.es-ES.vtt 238 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ar.vtt 238 B
Part 03-Module 01-Lesson 20_L8 Estimation/21. Point Estimate Engagement Ratio-R2a1wC3k0JM.en.vtt 237 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.en.vtt 237 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.pt-BR.vtt 237 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -5GuI-r2Dj1Y.en.vtt 237 B
Part 17-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-SYnYIjLpbjE.ja.vtt 237 B
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.en.vtt 236 B
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.zh-CN.vtt 236 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.ja.vtt 236 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.es-ES.vtt 236 B
Part 13-Module 01-Lesson 04_Design Principles/18. Thinking Fast-eSZ1kr_yZFg.zh-CN.vtt 235 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.en.vtt 234 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.pt-BR.vtt 234 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.en.vtt 234 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.ar.vtt 234 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.es-ES.vtt 234 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.it.vtt 234 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.es-ES.vtt 234 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.ar.vtt 234 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.en.vtt 233 B
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative--fGYnCkj20E.zh-CN.vtt 233 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.en.vtt 233 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-L9Wwg8AQk4M.pt-BR.vtt 233 B
Part 11-Module 01-Lesson 03_SVM/17. Separating with the New Feature-9KAHkienFWk.zh-CN.vtt 233 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.pt-BR.vtt 233 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.es-ES.vtt 233 B
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.pt-BR.vtt 232 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.ja.vtt 232 B
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.en.vtt 232 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.pt-BR.vtt 232 B
Part 11-Module 01-Lesson 13_PCA/01. Data Dimensionality-bAZJT4xHiXM.zh-CN.vtt 232 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.en.vtt 232 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.zh-CN.vtt 232 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-SJ9JldQSF5w.en.vtt 231 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.ar.vtt 231 B
Part 13-Module 01-Lesson 08_Animation and Interaction/18. Averaging Locations-bQQSqytU_r0.en.vtt 231 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.en.vtt 231 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.it.vtt 231 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.es-ES.vtt 231 B
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-4VKOJowrOoU.en.vtt 230 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/06. Mean of Sample Means-TpsMv7isR6U.zh-CN.vtt 230 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.pt-BR.vtt 230 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.pt-BR.vtt 230 B
Part 02-Module 01-Lesson 01_Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.zh-CN.vtt 229 B
Part 03-Module 01-Lesson 01_L1 Intro to Research Methods/21. True or Not-Ftk7_ipeZH8.zh-CN.vtt 229 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.en.vtt 229 B
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.pt-BR.vtt 229 B
Part 03-Module 01-Lesson 13_L5 Standardizing/06. Proportion Between 180 and 200-Ss00WF8qXHk.zh-CN.vtt 229 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.en.vtt 229 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-VXgMxs0tiBw.zh-CN.vtt 229 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-GCk9hNs1uxY.zh-CN.vtt 229 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.en.vtt 229 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.en.vtt 228 B
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.en.vtt 228 B
Part 03-Module 01-Lesson 20_L8 Estimation/11. Generalize Point Estimate-JveZxEnq9bI.zh-CN.vtt 228 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.pt-BR.vtt 228 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/14. Acne Medication - Decision-GCk9hNs1uxY.en.vtt 228 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.en.vtt 228 B
Part 11-Module 01-Lesson 02_Naive Bayes/31. Bayes Rule for Classification-oNTklG8dh-0.pt-BR.vtt 228 B
Part 17-Module 01-Lesson 04_Probability/06. Loaded Coin 3-HohMRlmHoMQ.zh-CN.vtt 228 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.zh-CN.vtt 228 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.th.vtt 228 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.es-ES.vtt 227 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.pt-BR.vtt 226 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.pt-BR.vtt 226 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.ja.vtt 226 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.ar.vtt 226 B
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.zh-CN.vtt 226 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.pt-BR.vtt 226 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.zh-CN.vtt 226 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-nEr-E8WZ-bo.en.vtt 225 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.ar.vtt 225 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.pt-BR.vtt 225 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.ja.vtt 225 B
Part 17-Module 01-Lesson 05_Binomial Distribution/05. 5 Flips 2 Heads-lhhUjxnbad8.zh-CN.vtt 225 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-3R0LfaKa-fw.pt-BR.vtt 224 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.es.vtt 224 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.es.vtt 224 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/20. Find the Median-zQzgB8KovNU.zh-CN.vtt 224 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.en.vtt 224 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.en.vtt 224 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.en.vtt 224 B
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.pt-BR.vtt 224 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.en.vtt 224 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.pt-BR.vtt 223 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.en.vtt 223 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.en.vtt 223 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.pt-BR.vtt 223 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-uZk43roQbt0.pt-BR.vtt 223 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-BR.vtt 223 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.pt-BR.vtt 223 B
Part 03-Module 01-Lesson 13_L5 Standardizing/05. Proportion Between 170 and 210-pX6RbiR-4PM.zh-CN.vtt 222 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-8mHK1E3mR4E.zh-CN.vtt 222 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t--ypzhIBAuvg.pt-BR.vtt 222 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-DvpOpY9ScQ0.zh-CN.vtt 222 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-U_FXY3uR4r0.en.vtt 222 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.en.vtt 222 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.zh-CN.vtt 222 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.zh-CN.vtt 222 B
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.pt-BR.vtt 222 B
Part 13-Module 01-Lesson 04_Design Principles/41. Size of the Effect in the Data-Z2bA98cBS4Q.zh-CN.vtt 222 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ar.vtt 222 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ar.vtt 222 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.en.vtt 222 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.ar.vtt 222 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.pt-BR.vtt 221 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.pt-BR.vtt 221 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.en.vtt 221 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.en.vtt 221 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/33. Probability of Obtaining Mean-wQ3iwH9b10w.zh-CN.vtt 221 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/36. Location of Mean-p3e965clFyU.zh-CN.vtt 221 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.pt-BR.vtt 221 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.en.vtt 221 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.pt-BR.vtt 221 B
Part 11-Module 01-Lesson 02_Naive Bayes/32. Chris or Sara-nNna_SLlIT8.en.vtt 221 B
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.es-ES.vtt 221 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.en.vtt 220 B
Part 03-Module 01-Lesson 11_L4 Variability/38. Bessel's Correction-fghrG_GXWhw.zh-CN.vtt 220 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.zh-Hans.vtt 220 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/17. Evidence to Reject the Null-BHRLT1tJXHU.zh-CN.vtt 220 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/37. Increase Engagement-o0gtllaVkuE.pt-BR.vtt 220 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.pt-BR.vtt 220 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/10. Gettysburg or Wilma-VMkt5knD4VU.zh-CN.vtt 220 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.en.vtt 220 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.en.vtt 220 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.ja.vtt 220 B
Part 11-Module 01-Lesson 07_Regressions/14. Predictions Using Regression-T-dTpFd7EO0.zh-CN.vtt 220 B
Part 11-Module 01-Lesson 11_Text Learning/02. Bag Of Words-QfIgUDXPhi8.en.vtt 220 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.pt-BR.vtt 219 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.en.vtt 219 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-ijy0n1EjY0M.zh-CN.vtt 219 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.pt-BR.vtt 219 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.en.vtt 219 B
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.ar.vtt 219 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ja.vtt 219 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.pt-BR.vtt 219 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.en.vtt 219 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.es-ES.vtt 219 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.en.vtt 219 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/21. Younger than 20-lNjXzIxTRmI.zh-CN.vtt 218 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-1Nn61ad1UOQ.en.vtt 218 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.ar.vtt 218 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.ar.vtt 218 B
Part 17-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-4YY-hmqSz30.pt-BR.vtt 218 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.zh-CN.vtt 218 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.ar.vtt 218 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.ar.vtt 218 B
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.en.vtt 217 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.pt-BR.vtt 217 B
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.pt-BR.vtt 217 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.en.vtt 217 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.ja.vtt 217 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.es-ES.vtt 217 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/05. Probability Less-1PkuYCWwc_g.zh-CN.vtt 216 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.en.vtt 216 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.hr.vtt 216 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.ja.vtt 216 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.zh-CN.vtt 216 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.pt-BR.vtt 216 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.en.vtt 216 B
Part 03-Module 01-Lesson 20_L8 Estimation/31. Probability Sample Mean Is at Least...-0r9S6UNDRu8.zh-CN.vtt 215 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/13. Two-Tailed Critical Values 0.01-Kb_OuJuCFH0.zh-CN.vtt 215 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/19. Finches - Decision-9cM-bc6aGTo.pt-BR.vtt 215 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-1Nn61ad1UOQ.pt-BR.vtt 215 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.pt-BR.vtt 215 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.pt-PT.vtt 215 B
Part 17-Module 01-Lesson 05_Binomial Distribution/07. 10 Flips 5 Heads-Qm4KTLfFMzo.zh-CN.vtt 215 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/07. Mode - Uniform Distribution-mFm0FfWHlXw.zh-CN.vtt 214 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.en.vtt 214 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.en.vtt 214 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/21. Visualize P-Value-GHw4SRGYd5Y.zh-CN.vtt 214 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.en.vtt 214 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron-MetxO9LDp-I.en.vtt 214 B
Part 17-Module 01-Lesson 05_Binomial Distribution/03. Heads Tails 2-S87Z5DgPJeo.en.vtt 214 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.en.vtt 214 B
Part 17-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-cdFrLeXIkZU.zh-CN.vtt 214 B
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.en.vtt 214 B
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.pt-BR.vtt 213 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/17. Price vs Carat and Color-ow70HVqX4OY.zh-CN.vtt 213 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.en.vtt 213 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.hr.vtt 213 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.it.vtt 213 B
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.en.vtt 213 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-b2t55uKFMrA.pt-BR.vtt 212 B
Part 09-Module 01-Lesson 02_R Basics/08. Demystifying R-Or9KvEd1flY.zh-CN.vtt 212 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/18. Color and Price--9CHGW25yMg.zh-CN.vtt 212 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.en.vtt 212 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.it.vtt 212 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.ja.vtt 212 B
Part 17-Module 01-Lesson 05_Binomial Distribution/14. Binomial 5-yof0QiP2mzk.zh-CN.vtt 212 B
Part 17-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Rf6WfB_1EJQ.zh-CN.vtt 212 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-a61GPGk-Qy4.pt-BR.vtt 212 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.es.vtt 211 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.ja.vtt 211 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.zh-CN.vtt 211 B
Part 13-Module 01-Lesson 02_D3 Building Blocks/09. -5GuI-r2Dj1Y.zh-CN.vtt 211 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ar.vtt 211 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.pt-BR.vtt 210 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/21. Median with Outlier-MFN6EMAzz_k.zh-CN.vtt 210 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.en.vtt 210 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.en.vtt 210 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.ar.vtt 210 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.en.vtt 210 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.es-ES.vtt 210 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.en.vtt 210 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.it.vtt 210 B
Part 17-Module 01-Lesson 05_Binomial Distribution/08. Formula-yTr8zCHdo5M.zh-CN.vtt 210 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.en.vtt 209 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/30. Sampling Distribution Shape-UMEckGyua6o.zh-CN.vtt 209 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.pt-BR.vtt 209 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.hr.vtt 209 B
Part 17-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.pt-BR.vtt 209 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.zh-CN.vtt 209 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.zh-CN.vtt 208 B
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.en.vtt 208 B
Part 03-Module 01-Lesson 13_L5 Standardizing/14. Andy - SDs Below-4VKOJowrOoU.zh-CN.vtt 208 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.en.vtt 208 B
Part 11-Module 01-Lesson 07_Regressions/02. Continuous Quiz-IC-fo_A0PxQ.zh-CN.vtt 208 B
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.en.vtt 208 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.ar.vtt 208 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/04. Probability Greater-SJ9JldQSF5w.zh-CN.vtt 207 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/37. Probability of Mean-dB5wr3taV7Y.zh-CN.vtt 207 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.en.vtt 207 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.en.vtt 207 B
Part 11-Module 01-Lesson 02_Naive Bayes/11. From Scatterplots to Predictions-SuGzxfoye9s.zh-CN.vtt 207 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.zh-CN.vtt 207 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.pt-BR.vtt 207 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.en.vtt 207 B
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.en.vtt 207 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ar.vtt 207 B
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.zh-CN.vtt 207 B
Part 18-Module 01-Lesson 01_Introduction to Data Wrangling/17. Assess Tidiness-LSdhieL7nXU.en.vtt 207 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-b2t55uKFMrA.en.vtt 206 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/08. Probability Mean or = 3-twcNden__9M.zh-CN.vtt 206 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.zh-CN.vtt 206 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-nEr-E8WZ-bo.pt-BR.vtt 206 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/14. Dependent Variable-nEr-E8WZ-bo.zh-CN.vtt 206 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-jNfrnjMn7dU.pt-BR.vtt 206 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/03. Scatterplot Review-W96zaGEma7o.zh-CN.vtt 206 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.pt-BR.vtt 206 B
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.zh-CN.vtt 206 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-DS_4EiegbtQ.en.vtt 205 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.pt-BR.vtt 205 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/24. t-Statistic-rWiQoVHAa0s.zh-CN.vtt 205 B
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.ja.vtt 205 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.ja.vtt 205 B
Part 11-Module 01-Lesson 07_Regressions/07. Income Continuous or Discrete-4yapJV56YoM.pt-BR.vtt 205 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.en.vtt 205 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.it.vtt 205 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.th.vtt 205 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.pt-BR.vtt 204 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-HruTS4wHpVQ.zh-CN.vtt 204 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.zh-CN.vtt 204 B
Part 11-Module 01-Lesson 09_Clustering/08. Handoff to Katie-knrPsGtpyQY.pt-BR.vtt 204 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.ar.vtt 204 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.zh-CN.vtt 204 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ar.vtt 204 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.hr.vtt 204 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.th.vtt 204 B
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.zh-CN.vtt 204 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/12. Bin Size-dSgIDN1gz5k.es.vtt 203 B
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.pt-BR.vtt 203 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.en.vtt 203 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.en.vtt 203 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.en.vtt 203 B
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.en.vtt 203 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-j0uDMc3Yrlo.en.vtt 203 B
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.ar.vtt 203 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/18. Bush Precision and Recall-8fM13xqU2a8.pt-BR.vtt 203 B
Part 17-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.pt-BR.vtt 203 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.pt-BR.vtt 202 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/25. Corrected Standard Error-ksf2wklgpZ8.zh-CN.vtt 202 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ar.vtt 202 B
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.pt-BR.vtt 202 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.ja.vtt 202 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.pt-BR.vtt 201 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/09. Between 118 and 226-b2t55uKFMrA.zh-CN.vtt 201 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.zh-CN.vtt 201 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/27. Reject or Fail to Reject-Nl5RzE-RQHA.pt-BR.vtt 201 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/21. t-Critical-uZk43roQbt0.zh-CN.vtt 201 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.pt-BR.vtt 201 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/16. Cut and Price-MZyle39D5Ks.zh-CN.vtt 201 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.pt-BR.vtt 201 B
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.en.vtt 201 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.en.vtt 201 B
Part 13-Module 01-Lesson 04_Design Principles/42. Size of the Effect in the Graphic-nahhIlT8uSs.zh-CN.vtt 201 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.ja.vtt 201 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.pt-BR.vtt 201 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/14. Two-Tailed Critical Values 0.001-sqOOrXKazFw.zh-CN.vtt 200 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson...-vwRvT9b7IEE.en.vtt 200 B
Part 11-Module 01-Lesson 04_Decision Trees/02. Linearly Separable Data-YNfxSsQT78Y.zh-CN.vtt 200 B
Part 17-Module 01-Lesson 07_Bayes Rule/28. Robot Sensing 8-hyAQ28MYmc4.ja.vtt 200 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.en.vtt 199 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/21. Shape of Distribution When n Increases-YT3sdKcl3Vg.en.vtt 199 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t--ypzhIBAuvg.zh-CN.vtt 199 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-z60KPEhRSYs.en.vtt 199 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-U_FXY3uR4r0.zh-CN.vtt 199 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.pt-BR.vtt 199 B
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations-pXfWdBuWw74.zh-CN.vtt 199 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.pt-BR.vtt 199 B
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.ja.vtt 199 B
Part 11-Module 01-Lesson 04_Decision Trees/30. Information Gain Calculation Part 9-PDqyWzZCVBY.en.vtt 199 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.ja.vtt 199 B
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.pt-BR.vtt 198 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-CtIN6dfd-h4.pt-BR.vtt 198 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.en.vtt 198 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-V96RcbbVP7Q.zh-CN.vtt 198 B
Part 17-Module 01-Lesson 07_Bayes Rule/24. Robot Sensing 4-d_fbDqAGVdE.ja.vtt 198 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/07. Compute r^2-ZEkbLbmfHvg.zh-CN.vtt 197 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/28. Meaningful Results-7LoVF_V0qZ4.zh-CN.vtt 197 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.zh-CN.vtt 197 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.hr.vtt 197 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.ja.vtt 197 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.ja.vtt 196 B
Part 11-Module 01-Lesson 04_Decision Trees/24. Information Gain Calculation Part 3-yWPbe8onCeA.pt-BR.vtt 196 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.ar.vtt 196 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.en.vtt 196 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.zh-CN.vtt 196 B
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.ar.vtt 196 B
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.pt-BR.vtt 195 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/22. SEM-Sv8q6DpXOA0.zh-CN.vtt 195 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-_BPrFUlWcXo.pt-BR.vtt 195 B
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.pt-BR.vtt 195 B
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.zh-CN.vtt 194 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/14. Increase t--ypzhIBAuvg.en.vtt 194 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/08. Calculate t-Statistic-aBdP9_JBhAs.zh-CN.vtt 194 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.en.vtt 194 B
Part 11-Module 01-Lesson 06_Datasets and Questions/05. Types of Data Quiz 1-j1vFBL3khh0.zh-CN.vtt 194 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.ja.vtt 194 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.ja.vtt 194 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.en.vtt 193 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/20. Percentage Under 60-SHAt1I_VNys.zh-CN.vtt 193 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson...-vwRvT9b7IEE.pt-BR.vtt 193 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.en.vtt 193 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.en.vtt 193 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.ja.vtt 193 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.en.vtt 192 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-58Mh3hOraqk.zh-CN.vtt 192 B
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.zh-CN.vtt 192 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.es-ES.vtt 192 B
Part 17-Module 01-Lesson 04_Probability/04. Loaded Coin 1-sNvQeSikRFY.zh-CN.vtt 192 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-RF_DpOg--PY.zh-CN.vtt 191 B
Part 03-Module 01-Lesson 11_L4 Variability/19. Average Deviation-4e4jMjA9pVk.zh-CN.vtt 191 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/25. Rent - Decision-s7JS53yUHN0.zh-CN.vtt 191 B
Part 11-Module 01-Lesson 02_Naive Bayes/10. Speed Scatterplot 3-PaE5caOJ5kg.zh-CN.vtt 191 B
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.zh-CN.vtt 191 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ar.vtt 191 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-z60KPEhRSYs.pt-BR.vtt 190 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/37. Keyboards - Decision-U_FXY3uR4r0.pt-BR.vtt 190 B
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.ja.vtt 190 B
Part 11-Module 01-Lesson 04_Decision Trees/18. Entropy Calculation Part 3-WmnGwUCW-Yc.zh-CN.vtt 190 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.en.vtt 190 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.ja.vtt 190 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ar.vtt 190 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.en.vtt 189 B
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.pt-BR.vtt 189 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/08. More than 262-ulXPRo2lgC8.zh-CN.vtt 189 B
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.zh-CN.vtt 189 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.pt-BR.vtt 189 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-Hans.vtt 189 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/23. Mean Difference-eTNZnE_O_RM.zh-CN.vtt 188 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/14. Clarity and Price-UnkrtPPx9-c.zh-CN.vtt 188 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.pt-BR.vtt 188 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.ar.vtt 188 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.pt-BR.vtt 188 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.pt-BR.vtt 188 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.es.vtt 187 B
Part 03-Module 01-Lesson 11_L4 Variability/05. Does Range Change-SLl0i0SKwHU.en.vtt 187 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/24. Rent - t-Statistic-A8xSEFaFuBc.zh-CN.vtt 187 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/35. Keyboards - t-Statistic-JwrCtWoPBjo.zh-CN.vtt 187 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.ar.vtt 187 B
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.ar.vtt 187 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.ja.vtt 187 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.zh-CN.vtt 187 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.it.vtt 187 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.ja.vtt 187 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.zh-CN.vtt 187 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/04. Mode of Dataset-HvOjcTFlVTI.zh-CN.vtt 186 B
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.en.vtt 186 B
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.pt-BR.vtt 186 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.en.vtt 186 B
Part 17-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.pt-BR.vtt 186 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-z2xsu2Kehyo.zh-CN.vtt 186 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.en.vtt 186 B
Part 03-Module 01-Lesson 11_L4 Variability/22. Absolute Deviations-pFyPTDVN41Q.zh-CN.vtt 185 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/26. P-Value-5pnYBObhGJk.zh-CN.vtt 185 B
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.pt-BR.vtt 185 B
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.en.vtt 185 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-GtiLFC7EgFE.zh-CN.vtt 185 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.es-ES.vtt 185 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.pt-BR.vtt 184 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-AdLGLYYYVao.pt-BR.vtt 184 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.ar.vtt 184 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.en.vtt 184 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ar.vtt 184 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.pt-BR.vtt 184 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ja.vtt 184 B
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations-pXfWdBuWw74.en.vtt 183 B
Part 09-Module 01-Lesson 09_Diamonds Price Predictions/15. Price vs Carat and Cut-RF9V7l00a28.zh-CN.vtt 183 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.pt-BR.vtt 183 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/35. To Finish This Lesson...-vwRvT9b7IEE.zh-CN.vtt 182 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-FBRK-XwPC54.zh-CN.vtt 182 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.en.vtt 182 B
Part 13-Module 01-Lesson 07_Narrative Structures/33. Steps in the Data Binding Process-rHBJuhoajXE.en.vtt 182 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-d4LWnxyvrTQ.zh-CN.vtt 182 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.en.vtt 182 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.zh-CN.vtt 181 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.ja.vtt 181 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.pt-BR.vtt 181 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.en.vtt 181 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.pt-BR.vtt 180 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/17. Find Bin Size-Qc81PeO-YYU.zh-CN.vtt 180 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/09. One-Tailed t-Test-ycVGpvTfoso.zh-CN.vtt 180 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/33. Keyboards Point Estimate for Difference-1Nn61ad1UOQ.zh-CN.vtt 180 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.pt-BR.vtt 180 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/22. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.zh-CN.vtt 180 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-pJrwiukN3Ls.zh-CN.vtt 180 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.en.vtt 180 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.ja.vtt 180 B
Part 17-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.zh-CN.vtt 180 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.es.vtt 178 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.en.vtt 178 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.it.vtt 178 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.th.vtt 178 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.en.vtt 178 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-ylUUpaUfFEY.pt-BR.vtt 177 B
Part 11-Module 01-Lesson 03_SVM/15. A New Feature-8TqVHRan4Fo.pt-BR.vtt 177 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.pt-BR.vtt 177 B
Part 11-Module 01-Lesson 07_Regressions/04. Weather Continuous or Discrete-jTKkq6DdJMw.zh-CN.vtt 177 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.pt-BR.vtt 177 B
Part 17-Module 01-Lesson 04_Probability/10. Two Flips 3-uimwo-puQWY.zh-CN.vtt 177 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.th.vtt 177 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.pt-BR.vtt 177 B
Part 11-Module 01-Lesson 02_Naive Bayes/09. Speed Scatterplot 2-T4GbEVybNlY.zh-CN.vtt 176 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.ar.vtt 176 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-CtIN6dfd-h4.ar.vtt 176 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ar.vtt 176 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ja.vtt 176 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.es.vtt 175 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.pt-BR.vtt 175 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-l86zVvAfjNA.pt-BR.vtt 175 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/36. Keyboards - t-Critical Values-DS_4EiegbtQ.zh-CN.vtt 175 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.ar.vtt 175 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.ja.vtt 175 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.en.vtt 174 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.es-ES.vtt 174 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.it.vtt 174 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.es-ES.vtt 174 B
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.en.vtt 174 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.es.vtt 173 B
Part 03-Module 01-Lesson 13_L5 Standardizing/03. Absolute or Relative-kQtW3r36-Lc.zh-CN.vtt 173 B
Part 03-Module 01-Lesson 13_L5 Standardizing/04. Relative Frequency Histogram-gPTaXk37UYY.zh-CN.vtt 173 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-_yD3iz4bFhc.pt-BR.vtt 173 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.pt-BR.vtt 173 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.it.vtt 173 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.pt-BR.vtt 173 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.pt-BR.vtt 173 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.pt-BR.vtt 173 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/12. Two-Tailed Probability-KwbK0InYgvE.zh-CN.vtt 172 B
Part 11-Module 01-Lesson 04_Decision Trees/25. Information Gain Calculation Part 4-i6aCKjMeZPk.zh-CN.vtt 172 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.es.vtt 171 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.ar.vtt 171 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.pt-BR.vtt 171 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.it.vtt 171 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.it.vtt 171 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.pt-BR.vtt 171 B
Part 03-Module 01-Lesson 11_L4 Variability/27. Average Squared Deviation-xW3JXTmUlEE.zh-CN.vtt 170 B
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.pt-BR.vtt 170 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.pt-BR.vtt 170 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.es-ES.vtt 170 B
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.pt-BR.vtt 170 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.zh-CN.vtt 169 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.pt-BR.vtt 169 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.en.vtt 169 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.pt-BR.vtt 169 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-y7Kk4Aywtrg.pt-BR.vtt 168 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.ar.vtt 168 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.pt-BR.vtt 168 B
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.en.vtt 167 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-8TeKzSUGAJQ.en.vtt 167 B
Part 11-Module 01-Lesson 13_PCA/08. Principal Axis of New Coordinate System-qPr3Uj55eog.zh-CN.vtt 167 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.pt-BR.vtt 167 B
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.ar.vtt 167 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.en.vtt 167 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.pt-BR.vtt 167 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/05. Critical Values 0.001-h72200GCyaI.zh-CN.vtt 166 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/20. Degrees of Freedom-GOwsOqdMY8w.zh-CN.vtt 166 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.zh-CN.vtt 166 B
Part 11-Module 01-Lesson 06_Datasets and Questions/08. Types of Data Quiz 4-wzNCL-MJ2bc.zh-CN.vtt 166 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.zh-CN.vtt 166 B
Part 11-Module 01-Lesson 10_Feature Scaling/07. Feature Scaling Formula Quiz 1-sPqs7DoBkXQ.zh-CN.vtt 166 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.ar.vtt 166 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.es-ES.vtt 166 B
Part 11-Module 01-Lesson 03_SVM/02. Separating Line-NTm_mA4akP4.ja.vtt 165 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.pt-BR.vtt 165 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-J6RyUyWxrM4.zh-CN.vtt 165 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.en.vtt 165 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.es-ES.vtt 165 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.pt-BR.vtt 164 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-OdsfV143AMc.en.vtt 164 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.zh-CN.vtt 164 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.th.vtt 164 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.it.vtt 164 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.pt-BR.vtt 164 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.pt-BR.vtt 164 B
Part 11-Module 01-Lesson 03_SVM/03. Choosing Between Separating Lines-ppSLADGROp8.en.vtt 163 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.hr.vtt 163 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.zh-CN.vtt 163 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.ar.vtt 163 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.es.vtt 162 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.pt-BR.vtt 162 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/20. False Positives in Eigenfaces-0bEbJ33dUis.en.vtt 161 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.ar.vtt 161 B
Part 17-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.en.vtt 161 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/16. Finches - n and DF-z60KPEhRSYs.zh-CN.vtt 160 B
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.pt-BR.vtt 160 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/06. Confusion Matrix Practice 1-Nn_8kCRYn2k.zh-CN.vtt 160 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.es-ES.vtt 160 B
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.pt-BR.vtt 160 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.th.vtt 160 B
Part 17-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.zh-CN.vtt 160 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-ferT-sqV3A0.pt-BR.vtt 159 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.pt-BR.vtt 159 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.pt-BR.vtt 159 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.ja.vtt 159 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.pt-BR.vtt 158 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.zh-CN.vtt 158 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.ar.vtt 158 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.zh-CN.vtt 158 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.es.vtt 157 B
Part 11-Module 01-Lesson 04_Decision Trees/20. Entropy Calculation Part 5-ZSkYbBsFuOQ.zh-CN.vtt 157 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.ar.vtt 157 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/11. Confusion Matrix for Eigenfaces-jkjr_prWyt8.zh-CN.vtt 157 B
Part 17-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.hr.vtt 157 B
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.ja.vtt 157 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.es-ES.vtt 157 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.pt-BR.vtt 157 B
Part 17-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.zh-CN.vtt 157 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.ko.vtt 156 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.ja.vtt 156 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.pt-BR.vtt 155 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.en.vtt 155 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.zh-CN.vtt 155 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.hr.vtt 155 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.ja.vtt 155 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.es-ES.vtt 155 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.en.vtt 155 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.pt-BR.vtt 155 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.ja.vtt 154 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.en.vtt 153 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.zh-CN.vtt 153 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.ar.vtt 153 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/16. Mean with Outlier-RaXs536nNkg.pt-BR.vtt 152 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/18. Shoes - t-Statistic-kJxLPlQC-lQ.zh-CN.vtt 152 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.ja.vtt 152 B
Part 11-Module 01-Lesson 04_Decision Trees/17. Entropy Calculation Part 2-3tzTP3e0Cjw.zh-CN.vtt 152 B
Part 17-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.zh-CN.vtt 152 B
Part 17-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.en.vtt 152 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.th.vtt 152 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ar.vtt 152 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.en.vtt 151 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.it.vtt 151 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.zh-CN.vtt 150 B
Part 17-Module 01-Lesson 05_Binomial Distribution/11. Binomial 2-Uy7b3aMPnEY.zh-CN.vtt 150 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.zh-CN.vtt 150 B
Part 05-Module 02-Lesson 07_Case study OpenStreetMap Data [SQL]/12. Congratulations-pXfWdBuWw74.pt-BR.vtt 149 B
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.ja.vtt 149 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.pt-BR.vtt 149 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.hr.vtt 149 B
Part 17-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.ja.vtt 149 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.pt-BR.vtt 149 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.zh-CN.vtt 149 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.zh-CN.vtt 149 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.en.vtt 148 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.en.vtt 147 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d--x9e6NP_ac0.pt-BR.vtt 147 B
Part 17-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.en.vtt 147 B
Part 17-Module 01-Lesson 05_Binomial Distribution/04. 5 Flips 1 Head-VEfOdACY9rA.en.vtt 146 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.pt-BR.vtt 146 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.es.vtt 144 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.zh-CN.vtt 144 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/06. Mode - Negatively Skewed Distribution-oNRtSJvtkJc.zh-CN.vtt 144 B
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.en.vtt 144 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.hr.vtt 144 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.ar.vtt 144 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.en.vtt 143 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.pt-BR.vtt 143 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.es-ES.vtt 143 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-jO81hfubpXY.en.vtt 142 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/12. How Many Schroeders-T2dveKB64Ho.zh-CN.vtt 142 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.es-ES.vtt 142 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.ja.vtt 142 B
Part 17-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.en.vtt 142 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.en.vtt 142 B
Part 17-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.zh-CN.vtt 142 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-ZeIYb60Qerk.en.vtt 141 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/26. Rent - Cohen's d-k7eajev401c.en.vtt 141 B
Part 11-Module 01-Lesson 10_Feature Scaling/03. Height + Weight for Cameron--dT9dztM-Lc.en.vtt 141 B
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.pt-BR.vtt 141 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.es-ES.vtt 141 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.ar.vtt 141 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.ja.vtt 141 B
Part 17-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.ja.vtt 141 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.es-ES.vtt 141 B
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.pt-BR.vtt 140 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-nG9l9ba7TrE.pt-BR.vtt 140 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/34. Does Low Probability = Causation-l86zVvAfjNA.en.vtt 140 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/05. SD for Meal Price-_BPrFUlWcXo.en.vtt 140 B
Part 11-Module 01-Lesson 10_Feature Scaling/02. A Metric for Chris-Thj7e55iSlA.en.vtt 140 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.ar.vtt 140 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.en.vtt 140 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.es-ES.vtt 140 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.en.vtt 139 B
Part 11-Module 01-Lesson 13_PCA/11. Practice Finding New Axes-th34aboBOO0.en.vtt 139 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.ja.vtt 139 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.en.vtt 138 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.en.vtt 138 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.it.vtt 138 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.ja.vtt 138 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.es-ES.vtt 138 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-dyShKWpTo-c.en.vtt 137 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.ja.vtt 137 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.th.vtt 137 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.en.vtt 137 B
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.en.vtt 136 B
Part 03-Module 01-Lesson 16_L6 Normal Distribution/10. Less than 240-ZeIYb60Qerk.pt-BR.vtt 136 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/28. Klout Sampling Distribution (Mean)-_yD3iz4bFhc.en.vtt 136 B
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.ar.vtt 136 B
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.zh-CN.vtt 136 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.en.vtt 136 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.th.vtt 135 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/20. Alternative Hypothesis-ferT-sqV3A0.en.vtt 134 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.pt-BR.vtt 134 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.ja.vtt 134 B
Part 11-Module 01-Lesson 15_Evaluation Metrics/21. False Negatives in Eigenfaces-dyShKWpTo-c.pt-BR.vtt 133 B
Part 17-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.pt-BR.vtt 133 B
[FreeCoursesOnline.Me].url 133 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.en.vtt 132 B
Part 03-Module 01-Lesson 30_L11 t-Tests, Part 3/24. Calculate Pooled Variance-jNfrnjMn7dU.en.vtt 132 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.ar.vtt 132 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.ja.vtt 132 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.ja.vtt 131 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.en.vtt 131 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.ja.vtt 131 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.es.vtt 130 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/29. Cohen's d--x9e6NP_ac0.en.vtt 130 B
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.pt-BR.vtt 130 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.en.vtt 130 B
Part 11-Module 01-Lesson 06_Datasets and Questions/09. Types of Data Quiz 5-dk3FxGVdP7Q.en.vtt 130 B
Part 13-Module 01-Lesson 04_Design Principles/43. Calculating the Lie Factor-CtIN6dfd-h4.en.vtt 130 B
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.es-ES.vtt 130 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.th.vtt 130 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.en.vtt 130 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.en.vtt 129 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/09. Range Percentages-fD6jd1ac3sk.en.vtt 129 B
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation-MNJlXsuCuyo.zh-CN.vtt 129 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.it.vtt 129 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.en.vtt 129 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.zh-CN.vtt 129 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.ar.vtt 129 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.es-ES.vtt 129 B
[FreeTutorials.Eu].url 129 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.zh-CN.vtt 128 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/27. Statistically Significant-y7Kk4Aywtrg.en.vtt 128 B
Part 11-Module 01-Lesson 02_Naive Bayes/08. Speed Scatterplot Grade and Bumpiness-v2UbL0SOm9A.en.vtt 128 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.en.vtt 128 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.pt-PT.vtt 127 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.zh-Hans.vtt 127 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.it.vtt 127 B
Part 17-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.zh-CN.vtt 127 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/08. Convert to Percentage-DVr1RodIqBw.zh-CN.vtt 126 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.en.vtt 126 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.zh-CN.vtt 126 B
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.ar.vtt 126 B
Part 17-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.zh-CN.vtt 126 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.ja.vtt 126 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ar.vtt 126 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/06. Sum Relative Frequencies-oxsmq36m5kQ.zh-CN.vtt 125 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-cJCx-Su6vx0.pt-BR.vtt 125 B
Part 11-Module 01-Lesson 06_Datasets and Questions/07. Types of Data Quiz 3-sMLnEgg2lqE.zh-CN.vtt 125 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.zh-CN.vtt 125 B
Part 11-Module 01-Lesson 13_PCA/02. Trickier Data Dimensionality--dcNhrSPmoY.zh-CN.vtt 125 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.es-ES.vtt 125 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.es-ES.vtt 125 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.pt-BR.vtt 125 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.pt-BR.vtt 124 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/18. Most Frequent Age-ypEVJhggHQc.zh-CN.vtt 123 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/29. Klout Sampling Distribution (SD)-ylUUpaUfFEY.en.vtt 123 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.ar.vtt 123 B
Part 17-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.zh-CN.vtt 123 B
Part 17-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.zh-CN.vtt 123 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.pt-BR.vtt 123 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.ja.vtt 123 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ja.vtt 123 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.fr.vtt 122 B
Part 03-Module 01-Lesson 28_L10b t-Tests, Part 2/30. r^2-L9Wwg8AQk4M.en.vtt 122 B
Part 11-Module 01-Lesson 04_Decision Trees/29. Information Gain Calculation Part 8-F-xSYJ3y_pA.pt-BR.vtt 122 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.ar.vtt 122 B
Part 17-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-1PHs2w_NNTg.en.vtt 122 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.ja.vtt 122 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.ar.vtt 122 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.pt-BR.vtt 122 B
Part 11-Module 01-Lesson 02_Naive Bayes/29. Total Probability-FlbDcNPGgUE.pt-BR.vtt 121 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.ar.vtt 121 B
Part 03-Module 01-Lesson 23_L9 Hypothesis Testing/37. Increase Engagement-o0gtllaVkuE.en.vtt 120 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.en.vtt 120 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.es-ES.vtt 120 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-SAdBKdiDE6w.en.vtt 119 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.es-AR.vtt 119 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.es-ES.vtt 119 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.ja.vtt 119 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-Hans.vtt 119 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.en.vtt 119 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.ar.vtt 118 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.en.vtt 118 B
Part 17-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.zh-CN.vtt 118 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.ar.vtt 118 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.es-ES.vtt 118 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.ja.vtt 118 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/19. Proportion over 60-u4rfZfA2ANk.zh-CN.vtt 117 B
Part 17-Module 01-Lesson 05_Binomial Distribution/02. Heads Tails-yo55zJtJQwo.zh-CN.vtt 117 B
Part 03-Module 01-Lesson 04_L2 Visualizing Data/05. Range of Proportions--xSSuPcrrA8.zh-CN.vtt 116 B
Part 03-Module 01-Lesson 11_L4 Variability/23. Average Absolute Deviation--S35dQNbjhc.zh-CN.vtt 116 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.en-GB.vtt 116 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ja.vtt 116 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.zh-CN.vtt 116 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.it.vtt 115 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.zh-CN.vtt 115 B
Part 03-Module 01-Lesson 20_L8 Estimation/32. What Does This Mean-Hqk1_dUlmo4.en.vtt 113 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.zh-CN.vtt 113 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.zh-CN.vtt 113 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.ja.vtt 113 B
Part 17-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.zh-CN.vtt 113 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/05. Mean of Each Sample-SAdBKdiDE6w.pt-BR.vtt 111 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.pt-BR.vtt 111 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.zh-CN.vtt 111 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.ar.vtt 110 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.pt-BR.vtt 110 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ar.vtt 110 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ja.vtt 110 B
Part 17-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.en.vtt 110 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.zh-CN.vtt 110 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-9TgKqnlta2U.pt-BR.vtt 109 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.en.vtt 109 B
Part 11-Module 01-Lesson 13_PCA/10. Practice Finding Centers-FZVBF1HR4U0.pt-BR.vtt 109 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.es-ES.vtt 109 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.es-ES.vtt 109 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.en.vtt 109 B
Part 11-Module 01-Lesson 04_Decision Trees/28. Information Gain Calculation Part 7-frzL4n6Y-vU.en.vtt 108 B
Part 11-Module 01-Lesson 10_Feature Scaling/08. Feature Scaling Formula Quiz 2-vmIK4jpUtNo.en.vtt 108 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.ar.vtt 108 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.th.vtt 108 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.pt-BR.vtt 108 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.es-ES.vtt 108 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.pt-BR.vtt 108 B
Part 17-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.zh-CN.vtt 108 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.en.vtt 107 B
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.ja.vtt 107 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.zh-CN.vtt 107 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.es-ES.vtt 107 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.pt-BR.vtt 106 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.ja.vtt 106 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.pt-BR.vtt 106 B
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.en.vtt 105 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.pt-BR.vtt 105 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.zh-CN.vtt 104 B
Part 03-Module 01-Lesson 18_L7 Sampling Distributions/11. Relationship Between SDs-nG9l9ba7TrE.en.vtt 104 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.ja.vtt 104 B
Part 11-Module 01-Lesson 10_Feature Scaling/04. Sarah's Height + Weight-p5p3OLARpmA.en.vtt 104 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.es-ES.vtt 104 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.en.vtt 104 B
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.zh-CN.vtt 103 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.en.vtt 103 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.en.vtt 101 B
Part 03-Module 01-Lesson 26_L10a t-Tests, Part 1/38. Keyboards - Cohen's d-9TgKqnlta2U.en.vtt 101 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.zh-CN.vtt 101 B
Part 11-Module 01-Lesson 04_Decision Trees/26. Information Gain Calculation Part 5-4oOXVejgFGk.en.vtt 101 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-BR.vtt 101 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-Hans.vtt 101 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.es-ES.vtt 101 B
Part 03-Module 01-Lesson 11_L4 Variability/31. Calculate SD-ZzEF7yc5208.pt-BR.vtt 100 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ja.vtt 100 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.pt-BR.vtt 100 B
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.ar.vtt 99 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.ar.vtt 99 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.pt-BR.vtt 99 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.zh-CN.vtt 99 B
Part 17-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.pt-BR.vtt 99 B
Part 03-Module 01-Lesson 08_L3 Central Tendency/19. Requirement for Median-T9tjPHqbB6M.es.vtt 98 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-Hans.vtt 98 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ar.vtt 98 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.zh-CN.vtt 98 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.pt-BR.vtt 97 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ja.vtt 97 B
Part 17-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.en.vtt 97 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.it.vtt 96 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.ar.vtt 96 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.es-ES.vtt 95 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.es-ES.vtt 95 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.en.vtt 95 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.hr.vtt 95 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ar.vtt 95 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.en.vtt 95 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.zh-CN.vtt 94 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ar.vtt 94 B
Part 17-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.it.vtt 94 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.ja.vtt 94 B
Part 17-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-ztkKTrMZHXg.pt-BR.vtt 94 B
Part 11-Module 01-Lesson 02_Naive Bayes/27. Normalizing 2-rnaZpqIqA2g.ar.vtt 93 B
Part 11-Module 01-Lesson 07_Regressions/03. Age Continuous or Discrete-kNxZwfXwvuk.en.vtt 92 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ar.vtt 92 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.pt-BR.vtt 92 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.pt-BR.vtt 91 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.ja.vtt 91 B
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.pt-BR.vtt 90 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.en.vtt 90 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.ar.vtt 90 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.zh-CN.vtt 90 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.en.vtt 90 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.it.vtt 90 B
Part 17-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.zh-CN.vtt 90 B
Part 11-Module 01-Lesson 02_Naive Bayes/28. Normalizing 3-L4elyDe8pFk.zh-CN.vtt 89 B
Part 11-Module 01-Lesson 04_Decision Trees/16. Entropy Calculation Part 1-JX3NN5zwL08.ja.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.it.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.pt-PT.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4-GD6cQhkoqS4.it.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.it.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.ja.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.pt-BR.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.pt-BR.vtt 89 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.en.vtt 89 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.en.vtt 88 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.it.vtt 88 B
Part 17-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.ja.vtt 88 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.ja.vtt 88 B
Part 17-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.hr.vtt 87 B
Part 17-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.it.vtt 87 B
Part 17-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2--pOzdj6pnbA.zh-CN.vtt 87 B
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