chainer.orgChainer: A flexible framework for neural networks

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chainer.org is a domain that was created on 2015-06-05,making it 9 years ago. It has several subdomains, such as docs.chainer.org , among others.

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chainer.org PopUrls

Chainer: A flexible framework for neural networks
https://chainer.org/
Chainer on Google Colaboratory
https://colab.chainer.org/
Chainer Blog
https://chainer.org/blog/
Chainer – A flexible framework of neural networks — Chainer ...
https://docs.chainer.org/
Chainer Blog
https://chainer.org/blog/2/
CuPy – NumPy & SciPy for GPU — CuPy 13.1.0 documentation
https://docs-cupy.chainer.org/
Chainer: A flexible framework for neural networks
https://chainer.org/blog/category/general/
Chainer – A flexible framework of neural networks
https://docs.chainer.org/en/latest/
A flexible framework for neural networks
https://chainer.org/blog/category/announcement/
Chainer – A flexible framework of neural networks
https://docs.chainer.org/en/stable/
Introduction to Chainer — Chainer 2.0.2 documentation
https://docs.chainer.org/en/v2.0.2/tutorial/basic.html
Chainer at a Glance — Chainer 7.8.1 documentation
https://docs.chainer.org/en/stable/glance.html
Chainer/CuPy v7 release and Future of Chainer
https://chainer.org/announcement/2019/12/05/released-v7.html
API Reference — Chainer 7.8.1 documentation
https://docs.chainer.org/en/stable/reference/
Installation — Chainer 7.8.1 documentation
http://docs.chainer.org/en/stable/install.html

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Blog Documentation GitHub Forum SlackA 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.gz tar xzf v7.8.1.tar.gz python chainer-7.8.1/examples/mnist/train_mnist.py Learn more from the official documentation . 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. Privacy Policy Design/Template: TEMPLATED , Cloud Cannon Photo: European Southern...

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