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This ecosystem page lists the projects that use MXNet, teach MXNet, or augment MXNet in some way.\n+\n+\n+## Highlighted Project\n+\n+[![Promo image](https://cdn-images-1.medium.com/max/800/1*PwIMdZM7tpt3rmcyhlk2FQ.png)](https://medium.com/apache-mxnet/announcing-keras-mxnet-v2-2-4b8404568e75)\n+#### [Keras-MXNet v2.2 released!](https://medium.com/apache-mxnet/announcing-keras-mxnet-v2-2-4b8404568e75)\n+\n+\n+## Contents\n+\n+* [Learning MXNet and other Educational Resources](#learning-mxnet-and-other-educational-resources)\n+* [MXNet APIs](#mxnet-apis)\n+* [Toolkits to Extend MXNet](#toolkits-to-extend-mxnet)\n+* [Debugging and Visualization](#debugging-and-visualization)\n+* [Model Serving](#model-serving)\n+* [Model Zoos](#model-zoos)\n+* [Contributions](#contributions)\n+\n+\n+## Learning MXNet and other Educational Resources\n+\n+* [Gluon 60 Minute Crash Course](https://gluon-crash-course.mxnet.io/) - deep learning practitioners can learn Gluon quickly with these six 10-minute tutorials.\n+    - [YouTube Series](https://www.youtube.com/playlist?list=PLkEvNnRk8uVmVKRDgznk3o3LxmjFRaW7s)\n+* [The Straight Dope](https://gluon.mxnet.io/) - a series of notebooks designed to teach deep learning using the Gluon Python API for MXNet.\n+\n+\n+## MXNet APIs\n+\n+* [Clojure API](https://github.com/apache/incubator-mxnet/tree/master/contrib/clojure-package) - use MXNet with Clojure.\n+* [C++ API](../api/c++/index.html) - not be confused with the C++ backend, this API allows C++ programmers to train networks in C++.\n+* [Gluon Python Interface](../gluon/index.html) - train complex models imperatively and then deploy with a symbolic graph.\n+* [Julia API](../api/julia/index.html) *(Community Supported)* - train models with multiple GPUs using Julia.\n+* [Keras-MXNet](https://github.com/awslabs/keras-apache-mxnet) - design with Keras2 and train with MXNet as the backend for 2x or more speed improvement.\n+* [MinPy](https://github.com/dmlc/minpy) - Pure numpy practice with third party operator integration and MXNet as backend for GPU computing\n+* [Module Python API](../api/python/index.html) - backed by the Symbol API, you can define your network in a declarative fashion.\n+* [ONNX-MXnet API](../api/python/contrib/onnx.html) - train and use Open Neural Network eXchange (ONNX) model files.\n+* [Perl API](../api/perl/index.html) *(Community Supported)* - train models with multiple GPUs using Perl.\n+* [R API](https://mxnet.incubator.apache.org/api/r/index.html) *(Community Supported)* - train models with multiple GPUs using R.\n+* [Scala Infer API](../api/scala/infer.html) - model loading and inference functionality.\n+* [TensorFuse](https://github.com/dementrock/tensorfuse) - Common interface for Theano, CGT, TensorFlow, and MXNet (experimental) by [dementrock](https://github.com/dementrock)\n+\n+\n+## Toolkits to Extend MXNet\n+\n+* [NVIDIA DALI](https://github.com/NVIDIA/DALI/tree/master/examples/mxnet) - a collection of highly optimized building 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is an I/O library that has MXNet plugin, so it's probably closer to being a dependency of 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