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[CourseClub.NET] Coursera - Neural Networks and Deep Learning
magnet:?xt=urn:btih:9d4ab63e818a10f7c0054d8dbe135e73f64ae06f&dn=[CourseClub.NET] Coursera - Neural Networks and Deep Learning
磁力链接详情
文件列表详情
9d4ab63e818a10f7c0054d8dbe135e73f64ae06f
infohash:
46
文件数量
877.57 MB
文件大小
2019-4-30 15:25
创建日期
2024-6-27 07:29
最后访问
相关分词
CourseClub
NET
Coursera
-
Neural
Networks
and
Deep
Learning
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
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.mp4 12.9 MB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.mp4 18.64 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.mp4 191.76 MB
004.Logistic Regression as a Neural Network/008. Binary Classification.mp4 15.24 MB
004.Logistic Regression as a Neural Network/009. Logistic Regression.mp4 8.48 MB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.mp4 13.19 MB
004.Logistic Regression as a Neural Network/011. Gradient Descent.mp4 17.05 MB
004.Logistic Regression as a Neural Network/012. Derivatives.mp4 13.41 MB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.mp4 16.76 MB
004.Logistic Regression as a Neural Network/014. Computation graph.mp4 5.66 MB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.mp4 21.69 MB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.mp4 11.15 MB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.mp4 12.17 MB
005.Python and Vectorization/018. Vectorization.mp4 12.6 MB
005.Python and Vectorization/019. More Vectorization Examples.mp4 10.34 MB
005.Python and Vectorization/020. Vectorizing Logistic Regression.mp4 11.46 MB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.mp4 15.55 MB
005.Python and Vectorization/022. Broadcasting in Python.mp4 16.17 MB
005.Python and Vectorization/023. A note on python numpy vectors.mp4 12.36 MB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.mp4 9.23 MB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).mp4 10.47 MB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.mp4 80.04 MB
007.Shallow Neural Network/027. Neural Networks Overview.mp4 7.23 MB
007.Shallow Neural Network/028. Neural Network Representation.mp4 8.26 MB
007.Shallow Neural Network/029. Computing a Neural Network's Output.mp4 16.32 MB
007.Shallow Neural Network/030. Vectorizing across multiple examples.mp4 13.86 MB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.mp4 11.97 MB
007.Shallow Neural Network/032. Activation functions.mp4 19.93 MB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.mp4 9.29 MB
007.Shallow Neural Network/034. Derivatives of activation functions.mp4 11.38 MB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.mp4 16.01 MB
007.Shallow Neural Network/036. Backpropagation intuition (optional).mp4 26.04 MB
007.Shallow Neural Network/037. Random Initialization.mp4 11.96 MB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.mp4 54.53 MB
009.Deep Neural Network/039. Deep L-layer neural network.mp4 10.35 MB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.mp4 13.02 MB
009.Deep Neural Network/041. Getting your matrix dimensions right.mp4 17.35 MB
009.Deep Neural Network/042. Why deep representations.mp4 17.59 MB
009.Deep Neural Network/043. Building blocks of deep neural networks.mp4 12.81 MB
009.Deep Neural Network/044. Forward and Backward Propagation.mp4 19.8 MB
009.Deep Neural Network/045. Parameters vs Hyperparameters.mp4 10.21 MB
009.Deep Neural Network/046. What does this have to do with the brain.mp4 6 MB
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