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Key Features &
Capabilities

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Hybrid Front-End

A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed.

Distributed Training

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.

Ecosystem

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

D2L.ai

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

GluonCV

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

GluonNLP

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

GluonTS

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

Community

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

GitHub

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

Discuss Forum

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

Slack

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

Original Source | Taken Source

APACHE MXNET: A FLEXIBLE AND EFFICIENT LIBRARY FOR DEEP LEARNING

Key Features &Capabilities