APACHE MXNET:
A FLEXIBLE AND EFFICIENT
LIBRARY FOR DEEP LEARNING

A truly open source deep learning framework suited
for flexible research prototyping and production.

Key Features &
Capabilities

All 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.

Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl.

A thriving ecosystem of tools and libraries extends MXNet and enable use-cases in computer vision, NLP, time series and more.

All Projects ›

Explore a rich ecosystem of libraries, tools, and more to support development.

An interactive deep learning book with code, math, and discussions. Used at Berkeley, University of Washington and more.

GluonCV is a computer vision toolkit with rich model zoo. From object detection to pose estimation.

GluonNLP provides state-of-the-art deep learning models in NLP. For engineers and researchers to fast prototype research ideas and products.

Gluon Time Series (GluonTS) is the Gluon toolkit for probabilistic time series modeling, focusing on deep learning-based models.

Join the Apache MXNet scientific community to contribute, learn, and get answers to your questions.

Report bugs, request features, discuss issues, and more.

Browse and join discussions on deep learning with MXNet and Gluon.

Discuss advanced topics. Request access by mail dev@mxnet.apache.org