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

Creation Time	Nov. 8, 2023, 9:57 p.m.
Last Access Time	Dec. 19, 2024, 5:41 a.m.
File Size	878.1 MB
Keywords	FreeCoursesOnline Me and Neural Coursera - Deep Learning Networks
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003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.mp4 191.8 MB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.mp4 80.0 MB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.mp4 54.5 MB
007.Shallow Neural Network/036. Backpropagation intuition (optional).mp4 26.0 MB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.mp4 21.7 MB
007.Shallow Neural Network/032. Activation functions.mp4 19.9 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 18.6 MB
009.Deep Neural Network/042. Why deep representations.mp4 17.6 MB
009.Deep Neural Network/041. Getting your matrix dimensions right.mp4 17.4 MB
004.Logistic Regression as a Neural Network/011. Gradient Descent.mp4 17.0 MB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.mp4 16.8 MB
007.Shallow Neural Network/029. Computing a Neural Network's Output.mp4 16.3 MB
005.Python and Vectorization/022. Broadcasting in Python.mp4 16.2 MB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.mp4 16.0 MB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.mp4 15.5 MB
004.Logistic Regression as a Neural Network/008. Binary Classification.mp4 15.2 MB
007.Shallow Neural Network/030. Vectorizing across multiple examples.mp4 13.9 MB
004.Logistic Regression as a Neural Network/012. Derivatives.mp4 13.4 MB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.mp4 13.2 MB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.mp4 13.0 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 12.8 MB
005.Python and Vectorization/018. Vectorization.mp4 12.6 MB
005.Python and Vectorization/023. A note on python numpy vectors.mp4 12.4 MB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.mp4 12.2 MB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.mp4 12.0 MB
007.Shallow Neural Network/037. Random Initialization.mp4 12.0 MB
005.Python and Vectorization/020. Vectorizing Logistic Regression.mp4 11.5 MB
007.Shallow Neural Network/034. Derivatives of activation functions.mp4 11.4 MB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.mp4 11.2 MB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).mp4 10.5 MB
009.Deep Neural Network/039. Deep L-layer neural network.mp4 10.3 MB
005.Python and Vectorization/019. More Vectorization Examples.mp4 10.3 MB
009.Deep Neural Network/045. Parameters vs Hyperparameters.mp4 10.2 MB
001.Welcome to the Deep Learning Specialization/001. Welcome.mp4 10.2 MB
002.Introduction to Deep Learning/002. What is a neural network.mp4 10.0 MB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.mp4 9.3 MB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.mp4 9.2 MB
004.Logistic Regression as a Neural Network/009. Logistic Regression.mp4 8.5 MB
007.Shallow Neural Network/028. Neural Network Representation.mp4 8.3 MB
007.Shallow Neural Network/027. Neural Networks Overview.mp4 7.2 MB
009.Deep Neural Network/046. What does this have to do with the brain.mp4 6.0 MB
004.Logistic Regression as a Neural Network/014. Computation graph.mp4 5.7 MB
002.Introduction to Deep Learning/005. About this Course.mp4 4.7 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 26.9 KB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.srt 23.1 KB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.srt 17.9 KB
007.Shallow Neural Network/036. Backpropagation intuition (optional).srt 17.7 KB
007.Shallow Neural Network/032. Activation functions.srt 17.0 KB
007.Shallow Neural Network/029. Computing a Neural Network's Output.srt 16.5 KB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.srt 16.3 KB
004.Logistic Regression as a Neural Network/011. Gradient Descent.srt 15.4 KB
009.Deep Neural Network/042. Why deep representations.srt 14.5 KB
005.Python and Vectorization/022. Broadcasting in Python.srt 14.0 KB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.srt 13.4 KB
009.Deep Neural Network/044. Forward and Backward Propagation.srt 13.4 KB
009.Deep Neural Network/045. Parameters vs Hyperparameters.srt 13.0 KB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.srt 12.9 KB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.srt 12.3 KB
004.Logistic Regression as a Neural Network/012. Derivatives.srt 12.0 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 11.4 KB
007.Shallow Neural Network/034. Derivatives of activation functions.srt 11.3 KB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.srt 11.0 KB
009.Deep Neural Network/043. Building blocks of deep neural networks.srt 10.9 KB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.srt 10.7 KB
004.Logistic Regression as a Neural Network/008. Binary Classification.srt 10.6 KB
007.Shallow Neural Network/037. Random Initialization.srt 10.4 KB
007.Shallow Neural Network/030. Vectorizing across multiple examples.srt 10.1 KB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.srt 9.9 KB
002.Introduction to Deep Learning/002. What is a neural network.srt 9.9 KB
005.Python and Vectorization/018. Vectorization.srt 9.6 KB
005.Python and Vectorization/020. Vectorizing Logistic Regression.srt 9.6 KB
005.Python and Vectorization/023. A note on python numpy vectors.srt 9.0 KB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.srt 9.0 KB
001.Welcome to the Deep Learning Specialization/001. Welcome.srt 8.8 KB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.srt 8.7 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 8.1 KB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.srt 7.7 KB
004.Logistic Regression as a Neural Network/009. Logistic Regression.srt 7.6 KB
009.Deep Neural Network/039. Deep L-layer neural network.srt 7.4 KB
005.Python and Vectorization/019. More Vectorization Examples.srt 7.4 KB
007.Shallow Neural Network/027. Neural Networks Overview.srt 6.6 KB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.srt 5.8 KB
009.Deep Neural Network/046. What does this have to do with the brain.srt 5.6 KB
002.Introduction to Deep Learning/005. About this Course.srt 4.3 KB
004.Logistic Regression as a Neural Network/014. Computation graph.srt 4.3 KB
002.Introduction to Deep Learning/006. Course Resources.srt 3.6 KB
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[FreeCoursesOnline.Me] Coursera - Neural Networks and Deep Learning

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