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文档列表

003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.mp4 201.1 MB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.mp4 83.9 MB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.mp4 57.2 MB
007.Shallow Neural Network/036. Backpropagation intuition (optional).mp4 27.3 MB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.mp4 22.7 MB
007.Shallow Neural Network/032. Activation functions.mp4 20.9 MB
009.Deep Neural Network/044. Forward and Backward Propagation.mp4 20.8 MB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.mp4 19.6 MB
009.Deep Neural Network/042. Why deep representations.mp4 18.4 MB
009.Deep Neural Network/041. Getting your matrix dimensions right.mp4 18.2 MB
004.Logistic Regression as a Neural Network/011. Gradient Descent.mp4 17.9 MB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.mp4 17.6 MB
007.Shallow Neural Network/029. Computing a Neural Network's Output.mp4 17.1 MB
005.Python and Vectorization/022. Broadcasting in Python.mp4 17.0 MB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.mp4 16.8 MB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.mp4 16.3 MB
004.Logistic Regression as a Neural Network/008. Binary Classification.mp4 16.0 MB
007.Shallow Neural Network/030. Vectorizing across multiple examples.mp4 14.5 MB
004.Logistic Regression as a Neural Network/012. Derivatives.mp4 14.1 MB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.mp4 13.8 MB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.mp4 13.7 MB
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.mp4 13.5 MB
009.Deep Neural Network/043. Building blocks of deep neural networks.mp4 13.4 MB
005.Python and Vectorization/018. Vectorization.mp4 13.2 MB
005.Python and Vectorization/023. A note on python numpy vectors.mp4 13.0 MB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.mp4 12.8 MB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.mp4 12.6 MB
007.Shallow Neural Network/037. Random Initialization.mp4 12.5 MB
005.Python and Vectorization/020. Vectorizing Logistic Regression.mp4 12.0 MB
007.Shallow Neural Network/034. Derivatives of activation functions.mp4 11.9 MB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.mp4 11.7 MB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).mp4 11.0 MB
009.Deep Neural Network/039. Deep L-layer neural network.mp4 10.8 MB
005.Python and Vectorization/019. More Vectorization Examples.mp4 10.8 MB
009.Deep Neural Network/045. Parameters vs Hyperparameters.mp4 10.7 MB
001.Welcome to the Deep Learning Specialization/001. Welcome.mp4 10.7 MB
002.Introduction to Deep Learning/002. What is a neural network.mp4 10.5 MB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.mp4 9.7 MB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.mp4 9.7 MB
004.Logistic Regression as a Neural Network/009. Logistic Regression.mp4 8.9 MB
007.Shallow Neural Network/028. Neural Network Representation.mp4 8.7 MB
007.Shallow Neural Network/027. Neural Networks Overview.mp4 7.6 MB
009.Deep Neural Network/046. What does this have to do with the brain.mp4 6.3 MB
004.Logistic Regression as a Neural Network/014. Computation graph.mp4 5.9 MB
002.Introduction to Deep Learning/005. About this Course.mp4 4.9 MB
002.Introduction to Deep Learning/006. Course Resources.mp4 2.6 MB
003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.srt 58.9 kB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.srt 27.5 kB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.srt 23.6 kB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.srt 18.3 kB
007.Shallow Neural Network/036. Backpropagation intuition (optional).srt 18.1 kB
007.Shallow Neural Network/032. Activation functions.srt 17.4 kB
007.Shallow Neural Network/029. Computing a Neural Network's Output.srt 16.9 kB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.srt 16.7 kB
004.Logistic Regression as a Neural Network/011. Gradient Descent.srt 15.7 kB
009.Deep Neural Network/042. Why deep representations.srt 14.9 kB
005.Python and Vectorization/022. Broadcasting in Python.srt 14.3 kB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.srt 13.8 kB
009.Deep Neural Network/044. Forward and Backward Propagation.srt 13.8 kB
009.Deep Neural Network/045. Parameters vs Hyperparameters.srt 13.3 kB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.srt 13.2 kB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.srt 12.6 kB
004.Logistic Regression as a Neural Network/012. Derivatives.srt 12.3 kB
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.srt 12.2 kB
009.Deep Neural Network/041. Getting your matrix dimensions right.srt 11.7 kB
007.Shallow Neural Network/034. Derivatives of activation functions.srt 11.6 kB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.srt 11.3 kB
009.Deep Neural Network/043. Building blocks of deep neural networks.srt 11.2 kB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.srt 11.0 kB
004.Logistic Regression as a Neural Network/008. Binary Classification.srt 10.8 kB
007.Shallow Neural Network/037. Random Initialization.srt 10.6 kB
007.Shallow Neural Network/030. Vectorizing across multiple examples.srt 10.3 kB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.srt 10.1 kB
002.Introduction to Deep Learning/002. What is a neural network.srt 10.1 kB
005.Python and Vectorization/018. Vectorization.srt 9.8 kB
005.Python and Vectorization/020. Vectorizing Logistic Regression.srt 9.8 kB
005.Python and Vectorization/023. A note on python numpy vectors.srt 9.3 kB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.srt 9.2 kB
001.Welcome to the Deep Learning Specialization/001. Welcome.srt 9.0 kB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.srt 8.9 kB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).srt 8.7 kB
007.Shallow Neural Network/028. Neural Network Representation.srt 8.3 kB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.srt 7.9 kB
004.Logistic Regression as a Neural Network/009. Logistic Regression.srt 7.7 kB
009.Deep Neural Network/039. Deep L-layer neural network.srt 7.6 kB
005.Python and Vectorization/019. More Vectorization Examples.srt 7.6 kB
007.Shallow Neural Network/027. Neural Networks Overview.srt 6.8 kB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.srt 5.9 kB
009.Deep Neural Network/046. What does this have to do with the brain.srt 5.8 kB
002.Introduction to Deep Learning/005. About this Course.srt 4.5 kB
004.Logistic Regression as a Neural Network/014. Computation graph.srt 4.4 kB
002.Introduction to Deep Learning/006. Course Resources.srt 3.7 kB
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