buggiant / mxnet

efficient, flexible, distributed deep learning framework

for Deep Learnning

MXNet is a deep learning framework designed for both efficiency and flexibility. It aims for people

• Who want to apply deep learning for applications. One can use only several lines of codes to create and train a neural network with high efficiency. Check our examples for more details.
• Who want to use it for research on deep learning. MXNet provides flexible programming interface for rapid prototyping. For example, check our tutorials for Python

Contents

• Documentation
• Build Instruction
• Features
• License

Features

• To Mix and Maximize
  • Mix all flavors of programming models to maximize flexiblity and efficiency.
• Lightweight and scalable
  • Minimum build dependency, scales to multi-GPU and ready toward distributed.
• Auto parallelization
  • Write numpy-style ndarray GPU programs, which will be automatically parallelized.
• Language agnostic
  • With support for python, c++, more to come.
• Cloud friendly
  • Directly load/save from S3, HDFS, AZure
• Easy extensibility
  • Extending no requirement on GPU programming.

Bug Reporting

• For reporting bugs please use the mxnet/issues page.

Contributing to MXNet

MXNet has been developed and used by a group of active community members. Everyone is more than welcome to contribute. It is a way to make the project better and more accessible to more users.

• Please add your name to CONTRIBUTORS.md after your patch has been merged.

License

© Contributors, 2015. Licensed under an Apache-2.0 license.