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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