         Deep Learning Neural Networks with Chainer培訓(xùn)

Introduction

Chainer vs Caffe vs Torch
Overview of Chainer features and components
Getting Started

Understanding the trainer structure
Installing Chainer, CuPy, and NumPy
Defining functions on variables
Training Neural Networks in Chainer

Constructing a computational graph
Running MNIST dataset examples
Updating parameters using an optimizer
Processing images to evaluate results
Working with GPUs in Chainer

Implementing recurrent neural networks
Using multiple GPUs for parallelization
Implementing Other Neural Network Models

Defining RNN models and running examples
Generating images with Deep Convolutional GAN
Running Reinforcement Learning examples
Troubleshooting

Summary and Conclusion