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

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878 MB

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09/24/18 at 8:32am GMT+1

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[COURSERA] NEURAL NETWORKS AND DEEP LEARNING [FCO]

About this course: If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new “superpower” that will let you build AI systems that just weren’t possible a few years ago. In this course, you will learn the foundations of deep learning. When you finish this class, you will: – Understand the major technology trends driving Deep Learning – Be able to build, train and apply fully connected deep neural networks – Know how to implement efficient (vectorized) neural networks – Understand the key parameters in a neural network’s architecture This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions. This is the first course of the Deep Learning Specialization.

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File list

[FreeCoursesOnline.Me] Coursera - Neural Networks and Deep Learning
001.Welcome to the Deep Learning Specialization/001. Welcome.mp4 10.2 MB
001.Welcome to the Deep Learning Specialization/001. Welcome.srt 8.8 KB
002.Introduction to Deep Learning/002. What is a neural network.mp4 10 MB
002.Introduction to Deep Learning/002. What is a neural network.srt 9.9 KB
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.mp4 12.9 MB
002.Introduction to Deep Learning/003. Supervised Learning with Neural Networks.srt 11.9 KB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.mp4 18.6 MB
002.Introduction to Deep Learning/004. Why is Deep Learning taking off.srt 17.9 KB
002.Introduction to Deep Learning/005. About this Course.mp4 4.7 MB
002.Introduction to Deep Learning/005. About this Course.srt 4.3 KB
002.Introduction to Deep Learning/006. Course Resources.mp4 2.5 MB
002.Introduction to Deep Learning/006. Course Resources.srt 3.6 KB
003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.mp4 191.8 MB
003.Heroes of Deep Learning (Optional)/007. Geoffrey Hinton interview.srt 57.5 KB
004.Logistic Regression as a Neural Network/008. Binary Classification.mp4 15.2 MB
004.Logistic Regression as a Neural Network/008. Binary Classification.srt 10.6 KB
004.Logistic Regression as a Neural Network/009. Logistic Regression.mp4 8.5 MB
004.Logistic Regression as a Neural Network/009. Logistic Regression.srt 7.6 KB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.mp4 13.2 MB
004.Logistic Regression as a Neural Network/010. Logistic Regression Cost Function.srt 11 KB
004.Logistic Regression as a Neural Network/011. Gradient Descent.mp4 17 MB
004.Logistic Regression as a Neural Network/011. Gradient Descent.srt 15.4 KB
004.Logistic Regression as a Neural Network/012. Derivatives.mp4 13.4 MB
004.Logistic Regression as a Neural Network/012. Derivatives.srt 12 KB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.mp4 16.8 MB
004.Logistic Regression as a Neural Network/013. More Derivative Examples.srt 12.9 KB
004.Logistic Regression as a Neural Network/014. Computation graph.mp4 5.7 MB
004.Logistic Regression as a Neural Network/014. Computation graph.srt 4.3 KB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.mp4 21.7 MB
004.Logistic Regression as a Neural Network/015. Derivatives with a Computation Graph.srt 16.3 KB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.mp4 11.2 MB
004.Logistic Regression as a Neural Network/016. Logistic Regression Gradient Descent.srt 9 KB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.mp4 12.2 MB
004.Logistic Regression as a Neural Network/017. Gradient Descent on m Examples.srt 12.3 KB
005.Python and Vectorization/018. Vectorization.mp4 12.6 MB
005.Python and Vectorization/018. Vectorization.srt 9.6 KB
005.Python and Vectorization/019. More Vectorization Examples.mp4 10.3 MB
005.Python and Vectorization/019. More Vectorization Examples.srt 7.4 KB
005.Python and Vectorization/020. Vectorizing Logistic Regression.mp4 11.5 MB
005.Python and Vectorization/020. Vectorizing Logistic Regression.srt 9.6 KB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.mp4 15.5 MB
005.Python and Vectorization/021. Vectorizing Logistic Regression's Gradient Output.srt 10.7 KB
005.Python and Vectorization/022. Broadcasting in Python.mp4 16.2 MB
005.Python and Vectorization/022. Broadcasting in Python.srt 14 KB
005.Python and Vectorization/023. A note on python numpy vectors.mp4 12.4 MB
005.Python and Vectorization/023. A note on python numpy vectors.srt 9 KB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.mp4 9.2 MB
005.Python and Vectorization/024. Quick tour of Jupyter iPython Notebooks.srt 5.8 KB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).mp4 10.5 MB
005.Python and Vectorization/025. Explanation of logistic regression cost function (optional).srt 8.5 KB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.mp4 80 MB
006.Heroes of Deep Learning (Optional)/026. Pieter Abbeel interview.srt 26.9 KB
007.Shallow Neural Network/027. Neural Networks Overview.mp4 7.2 MB
007.Shallow Neural Network/027. Neural Networks Overview.srt 6.6 KB
007.Shallow Neural Network/028. Neural Network Representation.mp4 8.3 MB
007.Shallow Neural Network/028. Neural Network Representation.srt 8.1 KB
007.Shallow Neural Network/029. Computing a Neural Network's Output.mp4 16.3 MB
007.Shallow Neural Network/029. Computing a Neural Network's Output.srt 16.5 KB
007.Shallow Neural Network/030. Vectorizing across multiple examples.mp4 13.9 MB
007.Shallow Neural Network/030. Vectorizing across multiple examples.srt 10.1 KB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.mp4 12 MB
007.Shallow Neural Network/031. Explanation for Vectorized Implementation.srt 8.7 KB
007.Shallow Neural Network/032. Activation functions.mp4 19.9 MB
007.Shallow Neural Network/032. Activation functions.srt 17 KB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.mp4 9.3 MB
007.Shallow Neural Network/033. Why do you need non-linear activation functions.srt 7.7 KB
007.Shallow Neural Network/034. Derivatives of activation functions.mp4 11.4 MB
007.Shallow Neural Network/034. Derivatives of activation functions.srt 11.3 KB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.mp4 16 MB
007.Shallow Neural Network/035. Gradient descent for Neural Networks.srt 13.4 KB
007.Shallow Neural Network/036. Backpropagation intuition (optional).mp4 26 MB
007.Shallow Neural Network/036. Backpropagation intuition (optional).srt 17.7 KB
007.Shallow Neural Network/037. Random Initialization.mp4 12 MB
007.Shallow Neural Network/037. Random Initialization.srt 10.4 KB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.mp4 54.5 MB
008.Heroes of Deep Learning (Optional)/038. Ian Goodfellow interview.srt 23.1 KB
009.Deep Neural Network/039. Deep L-layer neural network.mp4 10.3 MB
009.Deep Neural Network/039. Deep L-layer neural network.srt 7.4 KB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.mp4 13 MB
009.Deep Neural Network/040. Forward Propagation in a Deep Network.srt 9.9 KB
009.Deep Neural Network/041. Getting your matrix dimensions right.mp4 17.4 MB
009.Deep Neural Network/041. Getting your matrix dimensions right.srt 11.4 KB
009.Deep Neural Network/042. Why deep representations.mp4 17.6 MB
009.Deep Neural Network/042. Why deep representations.srt 14.5 KB
009.Deep Neural Network/043. Building blocks of deep neural networks.mp4 12.8 MB
009.Deep Neural Network/043. Building blocks of deep neural networks.srt 10.9 KB
009.Deep Neural Network/044. Forward and Backward Propagation.mp4 19.8 MB
009.Deep Neural Network/044. Forward and Backward Propagation.srt 13.4 KB
009.Deep Neural Network/045. Parameters vs Hyperparameters.mp4 10.2 MB
009.Deep Neural Network/045. Parameters vs Hyperparameters.srt 13 KB
009.Deep Neural Network/046. What does this have to do with the brain.mp4 6 MB
009.Deep Neural Network/046. What does this have to do with the brain.srt 5.6 KB

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