Chainer: A flexible framework for neural networks_Travel & Tourism

Home Blog Documentation GitHub Forum Slack About us A Powerful, Flexible, and Intuitive Framework for Neural Networks Get Started Learn More Important Chainer is under the maintenance phase. Read the blog. Bridge the gap between algorithms and implementations of deep learning Powerful Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. Flexible Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Intuitive Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug. Quick Start Install Chainer: pip install chainer Run the MNIST example: wget https://github.com/chainer/chainer/archive/v7.8.1.tar.gztar xzf v7.8.1.tar.gzpython chainer-7.8.1/examples/mnist/train_mnist.py Learn more from the official documentation. @CuPy_Team Extension Libraries A library that implements various state-of-the-art deep reinforcement algorithms. A collection of tools to train and run neural networks for computer vision tasks. Slides Introduction to Chainer Companies supporting Chainer © Preferred Networks, inc., Preferred Infrastructure, inc. All rights reserved. Design/Template: TEMPLATED, Cloud Cannon Photo: European Southern Observatory