Modern Deep Learning in Python

Modern Deep Learning in Python, Build with modern libraries like Tensorflow, Theano, Keras, PyTorch, CNTK, MXNet. Train faster with GPU on AWS.

• 4.5 (1,963 ratings)
• Created by Lazy Programmer Inc.
•  English [Auto-generated], Indonesian [Auto-generated], 6 more

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What you'll learn

• Apply momentum to backpropagation to train neural networks
• Apply adaptive learning rate procedures like AdaGrad, RMSprop, and Adam to backpropagation to train neural networks
• Understand the basic building blocks of Theano
• Build a neural network in Theano
• Understand the basic building blocks of TensorFlow
• Build a neural network in TensorFlow
• Build a neural network that performs well on the MNIST dataset
• Understand the difference between full gradient descent, batch gradient descent, and stochastic gradient descent
• Understand and implement dropout regularization in Theano and TensorFlow
• Understand and implement batch normalization in Theano and Tensorflow
• Write a neural network using Keras
• Write a neural network using PyTorch
• Write a neural network using CNTK
• Write a neural network using MXNet

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