Apache MXNet on AWS
Developer Guide

What Is Apache MXNet?

Apache MXNet (MXNet) is an open source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of platforms, from cloud infrastructure to mobile devices. It is highly scalable, which allows for fast model training, and it supports a flexible programming model and multiple languages.

The MXNet library is portable and lightweight. It scales seamlessly on multiple GPUs on multiple machines.

MXNet supports programming in various languages including Python, R, Scala, Julia, and Perl.

About This Guide

This guide focuses on setting up MXNet on AWS. It provides step-by-step instructions for launching an Amazon EC2 instance and setting up MXNet and its dependencies to configure a stable, secure, and high-performance execution environment for deep learning applications.

When working with large amounts of data, you might choose to run MXNet on a cluster of EC2 instances. This allows you to scale horizontally—to add as many EC2 instances as you need to scale the compute and memory resources.

AWS provides Deep Learning Amazon Machine Images (AMIs) and AWS CloudFormation templates optimized for both CPU and GPU EC2 instances. This guide explains how to set up MXNet on AWS using these AMIs and templates.

More Info

MXNet is an Apache open source project. For more information about MXNet, see the following open source documentation:

  • Getting Started – Provides details for setting up MXNet on various platforms, such as macOS, Windows, and Linux. It also explains how to set up MXNet for use with different front-end languages, such as Python, Scala, R, Julia, and Perl.

  • Tutorials – Provides step-by-step procedures for various deep learning tasks using MXNet.

  • API Reference – For more information, see MXNet. At the top of this page, choose a language from the API menu.

For all other information, see MXNet.

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