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003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.mp4 191.76 MB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.mp4 80.04 MB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.mp4 54.53 MB
007.Shallow Neural Network/036. Backpropagation intuition (optional).mp4 26.04 MB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.mp4 21.69 MB
007.Shallow Neural Network/032. Activation functions.mp4 19.93 MB
009.Deep Neural Network/044. Forward and Backward Propagation.mp4 19.8 MB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.mp4 18.64 MB
009.Deep Neural Network/042. Why deep representations.mp4 17.59 MB
009.Deep Neural Network/041. Getting your matrix dimensions right.mp4 17.35 MB
004.Logistic Regression as a Neural Network/011. Gradient Descent.mp4 17.05 MB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.mp4 16.76 MB
007.Shallow Neural Network/029. Computing a Neural Network's Output.mp4 16.32 MB
005.Python and Vectorization/022. Broadcasting in Python.mp4 16.17 MB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.mp4 16.01 MB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.mp4 15.55 MB
004.Logistic Regression as a Neural Network/008. Binary Classification.mp4 15.24 MB
007.Shallow Neural Network/030. Vectorizing across multiple examples.mp4 13.86 MB
004.Logistic Regression as a Neural Network/012. Derivatives.mp4 13.41 MB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.mp4 13.19 MB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.mp4 13.02 MB
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.mp4 12.9 MB
009.Deep Neural Network/043. Building blocks of deep neural networks.mp4 12.81 MB
005.Python and Vectorization/018. Vectorization.mp4 12.6 MB
005.Python and Vectorization/023. A note on python numpy vectors.mp4 12.36 MB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.mp4 12.17 MB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.mp4 11.97 MB
007.Shallow Neural Network/037. Random Initialization.mp4 11.96 MB
005.Python and Vectorization/020. Vectorizing Logistic Regression.mp4 11.46 MB
007.Shallow Neural Network/034. Derivatives of activation functions.mp4 11.38 MB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.mp4 11.15 MB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).mp4 10.47 MB
009.Deep Neural Network/039. Deep L-layer neural network.mp4 10.35 MB
005.Python and Vectorization/019. More Vectorization Examples.mp4 10.34 MB
009.Deep Neural Network/045. Parameters vs Hyperparameters.mp4 10.21 MB
001.Welcome to the Deep Learning Specialization/001. Welcome.mp4 10.21 MB
002.Introduction to Deep Learning/002. What is a neural network.mp4 9.97 MB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.mp4 9.29 MB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.mp4 9.23 MB
004.Logistic Regression as a Neural Network/009. Logistic Regression.mp4 8.48 MB
007.Shallow Neural Network/028. Neural Network Representation.mp4 8.26 MB
007.Shallow Neural Network/027. Neural Networks Overview.mp4 7.23 MB
009.Deep Neural Network/046. What does this have to do with the brain.mp4 6 MB
004.Logistic Regression as a Neural Network/014. Computation graph.mp4 5.66 MB
002.Introduction to Deep Learning/005. About this Course.mp4 4.66 MB
002.Introduction to Deep Learning/006. Course Resources.mp4 2.5 MB
003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.srt 57.5 KB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.srt 26.86 KB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.srt 23.08 KB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.srt 17.85 KB
007.Shallow Neural Network/036. Backpropagation intuition (optional).srt 17.72 KB
007.Shallow Neural Network/032. Activation functions.srt 17.03 KB
007.Shallow Neural Network/029. Computing a Neural Network's Output.srt 16.52 KB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.srt 16.31 KB
004.Logistic Regression as a Neural Network/011. Gradient Descent.srt 15.36 KB
009.Deep Neural Network/042. Why deep representations.srt 14.53 KB
005.Python and Vectorization/022. Broadcasting in Python.srt 14 KB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.srt 13.44 KB
009.Deep Neural Network/044. Forward and Backward Propagation.srt 13.43 KB
009.Deep Neural Network/045. Parameters vs Hyperparameters.srt 13 KB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.srt 12.87 KB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.srt 12.29 KB
004.Logistic Regression as a Neural Network/012. Derivatives.srt 12.01 KB
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.srt 11.9 KB
009.Deep Neural Network/041. Getting your matrix dimensions right.srt 11.43 KB
007.Shallow Neural Network/034. Derivatives of activation functions.srt 11.29 KB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.srt 11 KB
009.Deep Neural Network/043. Building blocks of deep neural networks.srt 10.91 KB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.srt 10.74 KB
004.Logistic Regression as a Neural Network/008. Binary Classification.srt 10.57 KB
007.Shallow Neural Network/037. Random Initialization.srt 10.39 KB
007.Shallow Neural Network/030. Vectorizing across multiple examples.srt 10.06 KB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.srt 9.89 KB
002.Introduction to Deep Learning/002. What is a neural network.srt 9.86 KB
005.Python and Vectorization/018. Vectorization.srt 9.62 KB
005.Python and Vectorization/020. Vectorizing Logistic Regression.srt 9.59 KB
005.Python and Vectorization/023. A note on python numpy vectors.srt 9.04 KB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.srt 8.97 KB
001.Welcome to the Deep Learning Specialization/001. Welcome.srt 8.83 KB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.srt 8.67 KB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).srt 8.5 KB
007.Shallow Neural Network/028. Neural Network Representation.srt 8.09 KB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.srt 7.74 KB
004.Logistic Regression as a Neural Network/009. Logistic Regression.srt 7.56 KB
009.Deep Neural Network/039. Deep L-layer neural network.srt 7.4 KB
005.Python and Vectorization/019. More Vectorization Examples.srt 7.39 KB
007.Shallow Neural Network/027. Neural Networks Overview.srt 6.61 KB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.srt 5.78 KB
009.Deep Neural Network/046. What does this have to do with the brain.srt 5.64 KB
002.Introduction to Deep Learning/005. About this Course.srt 4.35 KB
004.Logistic Regression as a Neural Network/014. Computation graph.srt 4.29 KB
002.Introduction to Deep Learning/006. Course Resources.srt 3.63 KB
[FCS Forum].url 133 B
[FreeCourseSite.com].url 127 B
[CourseClub.NET].url 123 B
[DesireCourse.Com].url 51 B
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