課程大綱： Deep Learning Neural Networks with Chainer培訓
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
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