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[FreeCoursesOnline.Me] Coursera - Neural Networks and Deep Learning
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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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133 Bytes
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119 Bytes
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