Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.

Features

  • Design notes providing useful insights that can re-used by other DL projects
  • Flexible configuration for arbitrary computation graph
  • Mix and match imperative and symbolic programming to maximize flexibility and efficiency
  • Lightweight, memory efficient and portable to smart devices
  • Scales up to multi GPUs and distributed setting with auto parallelism
  • Support for Python, Scala, C++, Java, Clojure, R, Go, Javascript, Perl, Matlab, and Julia
  • Cloud-friendly and directly compatible with AWS S3, AWS Deep Learning AMI, AWS SageMaker, HDFS, and Azure

Project Samples

Play Video Hybrid Front-End Distributed Training - support for Horovod, a distributed learning framework

Project Activity

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Categories

Frameworks, Machine Learning, Deep Learning Frameworks

License

Apache License V2.0

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Frameworks, Python Machine Learning Software, Python Deep Learning Frameworks

Registered

2020-02-21
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