Highlighted Project¶

Contents¶

• Learning MXNet and other Educational Resources
• MXNet APIs
• Toolkits to Extend MXNet
• Debugging and Visualization
• Model Serving
• Model Zoos
• Contributions

Learning MXNet and other Educational Resources¶

• Gluon 60 Minute Crash Course - deep learning practitioners can learn Gluon quickly with these six 10-minute tutorials.

  • YouTube Series

• Dive into Deep Learning - a series of notebooks designed to teach deep learning using the Gluon Python API for MXNet.

MXNet APIs¶

• Clojure API - use MXNet with Clojure.
• C++ API - not be confused with the C++ backend, this API allows C++ programmers to train networks in C++.
• Gluon Python Interface - train complex models imperatively and then deploy with a symbolic graph.
• Julia API (Community Supported) - train models with multiple GPUs using Julia.
• Keras-MXNet - design with Keras2 and train with MXNet as the backend for 2x or more speed improvement.
• MinPy - Pure numpy practice with third party operator integration and MXNet as backend for GPU computing
• Module Python API - backed by the Symbol API, you can define your network in a declarative fashion.
• ONNX-MXnet API - train and use Open Neural Network eXchange (ONNX) model files.
• Perl API (Community Supported) - train models with multiple GPUs using Perl.
• R API (Community Supported) - train models with multiple GPUs using R.
• Scala Infer API - model loading and inference functionality.
• TensorFuse - Common interface for Theano, CGT, TensorFlow, and MXNet (experimental) by dementrock

Toolkits to Extend MXNet¶

• Gluon CV - state-of-the-art deep learning algorithms in computer vision.
• Gluon NLP - state-of-the-art deep learning models in natural language processing.
• Sockeye - a sequence-to-sequence framework for Neural Machine Translation

Debugging and Visualization¶

• MXBoard - lets you to visually inspect and interpret your MXNet runs and graphs using the TensorBoard software.

Model Serving¶

• MXNet Model Server (MMS) - simple yet scalable solution for model inference.

Model Zoos¶

• Gluon Model Zoo - models trained in Gluon and available through Gluon’s model zoo API.
• ONNX Model Zoo - ONNX models from a variety of ONNX-supported frameworks.

Contributions¶

Do you know of a project or resource in the MXNet ecosystem that should be listed here? Or would you like to get involved by providing your own contribution? Check out the guide for contributing to MXNet, and browse the design proposals to see what others are working on. You might find something you would like to help with or use those design docs as a template for your own proposal. Use one of the developer communication channels if you would like to know more, or create a GitHub issue if you would like to propose something for the MXNet ecosystem.