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Chapter 3 Deep Neural Network (DNN) Overview

от Mohammed Shalgham 1,142,497 KB • 45 файлов

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001. Why PyTorch.mp4
002. PyTorch Installation and Tensors Introduction.mp4
003. Automatic Differentiation PyTorch New.mp4
004. Why DNNs in Machine Learning.mp4
006. Perceptron.mp4
007. Perceptron Exercise.mp4
008. Perceptron Exercise Solution.mp4
009. Perceptron Implementation.mp4
010. DNN Architecture.mp4
011. DNN Architecture Exercise.mp4
012. DNN Architecture Exercise Solution.mp4
013. DNN Forward Step Implementation.mp4
014. DNN Why Activation Function Is Required.mp4
015. DNN Why Activation Function Is Required Exercise.mp4
017. DNN Properties of Activation Function.mp4
018. DNN Activation Functions in PyTorch.mp4
019. DNN What Is Loss Function.mp4
020. DNN What Is Loss Function Exercise.mp4
021. DNN What Is Loss Function Exercise Solution.mp4
022. DNN What Is Loss Function Exercise 02.mp4
023. DNN What Is Loss Function Exercise 02 Solution.mp4
024. DNN Loss Function in PyTorch.mp4
025. DNN Gradient Descent.mp4
026. DNN Gradient Descent Exercise.mp4
027. DNN Gradient Descent Exercise Solution.mp4
028. DNN Gradient Descent Implementation.mp4
029. DNN Gradient Descent Stochastic Batch Minibatch.mp4
030. DNN Gradient Descent Summary.mp4

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