Apache MXNet | A flexible and efficient library for deep learning. | Website analytics by TrustRadar
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Apache MXNet | A flexible and efficient library for deep learning.

A flexible and efficient library for deep learning.

Apache MXNet (incubating) is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines.

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Founded in

2017

Supported Languages

English, etc

Website Key Features

Dynamic Dependency Scheduler

Automatically parallelizes both symbolic and imperative operations on the fly for maximum efficiency.

Graph Optimization

Enhances symbolic execution speed and memory efficiency through advanced graph optimization techniques.

Portability

Lightweight and scalable, MXNet can effectively scale to multiple GPUs and machines.

Flexible Programming Models

Supports both symbolic and imperative programming to maximize productivity and efficiency.

Multi-GPU Support

Efficiently scales across multiple GPUs to accelerate deep learning tasks.

Multi-Language Support

Offers APIs in multiple programming languages, making it accessible to a wide range of developers.

Extensive Library

Comes with a comprehensive library of pre-built models and algorithms for various deep learning tasks.

Community Support

Backed by a vibrant community of developers and researchers contributing to its continuous improvement.

Additional information

License

Apache License 2.0

Repository

https://github.com/apache/incubator-mxnet

Documentation

Comprehensive documentation available at https://mxnet.apache.org/versions/1.8.0/

Community and Support

MXNet has a strong community support system including forums, mailing lists, and chat rooms for real-time discussions.

Contributing

MXNet welcomes contributions from the community. Guidelines for contributing can be found in the project's repository.

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