The Amazon Deep Learning AMIs provide pre-configured environments for machine learning developers and data scientists to quickly start experimenting with deep learning models. The AMIs now come with support for Chainer, a flexible and intuitive framework for neural networks. Chainer uses a "define-by-run" approach that enables developers to define their deep learning network architecture on the fly. Such dynamic computational graphs are especially helpful while working with recurrent neural networks (RNNs), and with inputs of variable length like in natural language processing. This release also includes PyTorch 0.3.1 and Apache MXNet 1.1 which provide performance enhancements and bug fixes.

You can find the Deep Learning AMI of your choice in the Quick Start section of the Step 1: Choose an Amazon Machine Image (AMI) in the EC2 instance launch wizard. Also visit our Documentation guide for help with selecting the right AMI for your project, simple tutorials and more resources.