Summary
Apache MXNet is a flexible and efficient open-source library for deep learning that supports research prototyping and production, with hybrid front-end, distributed training, multiple language bindings, and a rich ecosystem of tools and libraries.
Abstract
Apache MXNet is a truly open-source deep learning framework that offers flexibility and efficiency for both research and production purposes. Its hybrid front-end enables seamless transitions between imperative and symbolic modes, while its distributed training feature supports scalable performance optimization. MXNet supports eight programming languages and offers a wide range of tools and libraries for various use-cases, including computer vision, natural language processing, and time series. The MXNet ecosystem includes a rich set of projects, such as D2L.ai, GluonCV, GluonNLP, and GluonTS, which support development and learning in deep learning. The MXNet community is active and welcomes contributions, discussions, and feedback through various channels, including GitHub, discussion forum, and Slack.
Bullet Points
- •Flexible and efficient open-source deep learning framework
- •Hybrid front-end for seamless transitions between imperative and symbolic modes
- •Scalable distributed training and performance optimization
- •Supports eight programming languages
- •Rich ecosystem of tools and libraries for various use-cases
- •Active community for contributions, discussions, and feedback.