A FLEXIBLE AND EFFICIENT
LIBRARY FOR DEEP LEARNING
A truly open source deep learning framework suited
for flexible research prototyping and production.
Key Features &
A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed.
Scalable distributed training and performance optimization in research and production is enabled by the dual Parameter Server and Horovod support.
8 Language Bindings
Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl.
Tools & Libraries
A thriving ecosystem of tools and libraries extends MXNet and enable use-cases in computer vision, NLP, time series and more.
Explore a rich ecosystem of libraries, tools, and more to support development.
Join the Apache MXNet scientific community to contribute, learn, and get answers to your questions.