szha closed pull request #11528: New ecosystem website page
URL: https://github.com/apache/incubator-mxnet/pull/11528
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diff --git a/docs/_static/mxnet-theme/navbar.html
b/docs/_static/mxnet-theme/navbar.html
index 05ec5c42ce3..6588ec0cca8 100644
--- a/docs/_static/mxnet-theme/navbar.html
+++ b/docs/_static/mxnet-theme/navbar.html
@@ -43,12 +43,14 @@ <h1 id="logo-wrap">
<a href="#" class="main-nav-link dropdown-toggle"
data-toggle="dropdown" role="button" aria-haspopup="true"
aria-expanded="true">Community <span class="caret"></span></a>
<ul id="package-dropdown-menu-community" class="dropdown-menu
navbar-menu">
<li><a class="main-nav-link"
href="http://discuss.mxnet.io";>Forum</a></li>
- <li><a class="main-nav-link"
href="https://github.com/apache/incubator-mxnet";>Github</a></li>
+ <li><a class="main-nav-link"
href="https://github.com/apache/incubator-mxnet";>Github</a></li>
<li><a class="main-nav-link"
href="{{url_root}}community/contribute.html">Contribute</a></li>
+ <li><a class="main-nav-link"
href="{{url_root}}community/ecosystem.html">Ecosystem</a></li>
<li><a class="main-nav-link"
href="{{url_root}}community/powered_by.html">Powered By</a></li>
</ul>
</span>
</nav>
+
<script> function getRootPath(){ return "{{url_root}}" } </script>
<div class="burgerIcon dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown"
role="button">☰</a>
@@ -61,6 +63,7 @@ <h1 id="logo-wrap">
<li><a tabindex="-1"
href="http://discuss.mxnet.io";>Forum</a></li>
<li><a tabindex="-1"
href="https://github.com/apache/incubator-mxnet";>Github</a></li>
<li><a tabindex="-1"
href="{{url_root}}community/contribute.html">Contribute</a></li>
+ <li><a tabindex="-1"
href="{{url_root}}community/ecosystem.html">Ecosystem</a></li>
<li><a tabindex="-1"
href="{{url_root}}community/powered_by.html">Powered By</a></li>
</ul>
</li>
@@ -85,8 +88,7 @@ <h1 id="logo-wrap">
<li><a tabindex="-1"
href="{{url_root}}api/python/gluon/model_zoo.html">Gluon Model Zoo</a></li>
</ul>
</li>
- <li><a
href="{{url_root}}architecture/index.html">Architecture</a></li>
- <li><a class="main-nav-link"
href="https://github.com/dmlc/mxnet";>Github</a></li>
+ <li><a class="main-nav-link"
href="https://github.com/dmlc/mxnet";>Github</a></li>
</ul>
</div>
<div class="plusIcon dropdown">
diff --git a/docs/community/ecosystem.md b/docs/community/ecosystem.md
new file mode 100644
index 00000000000..5ca6d7a0b47
--- /dev/null
+++ b/docs/community/ecosystem.md
@@ -0,0 +1,71 @@
+# MXNet's Ecosystem
+
+Community contributions to MXNet have added many new valuable features and
functionality to support use cases such as model serving & portability, easy
and flexible APIs, and educational material like crash courses and online
books. This ecosystem page lists the projects that use MXNet, teach MXNet, or
augment MXNet in some way.
+
+
+## Highlighted Project
+
+[](https://medium.com/apache-mxnet/announcing-keras-mxnet-v2-2-4b8404568e75)
+#### [Keras-MXNet v2.2
released!](https://medium.com/apache-mxnet/announcing-keras-mxnet-v2-2-4b8404568e75)
+
+
+## Contents
+
+* [Learning MXNet and other Educational
Resources](#learning-mxnet-and-other-educational-resources)
+* [MXNet APIs](#mxnet-apis)
+* [Toolkits to Extend MXNet](#toolkits-to-extend-mxnet)
+* [Debugging and Visualization](#debugging-and-visualization)
+* [Model Serving](#model-serving)
+* [Model Zoos](#model-zoos)
+* [Contributions](#contributions)
+
+
+## Learning MXNet and other Educational Resources
+
+* [Gluon 60 Minute Crash Course](https://gluon-crash-course.mxnet.io/) - deep
learning practitioners can learn Gluon quickly with these six 10-minute
tutorials.
+ - [YouTube
Series](https://www.youtube.com/playlist?list=PLkEvNnRk8uVmVKRDgznk3o3LxmjFRaW7s)
+* [The Straight Dope](https://gluon.mxnet.io/) - a series of notebooks
designed to teach deep learning using the Gluon Python API for MXNet.
+
+
+## MXNet APIs
+
+* [Clojure
API](https://github.com/apache/incubator-mxnet/tree/master/contrib/clojure-package)
- use MXNet with Clojure.
+* [C++ API](../api/c++/index.html) - not be confused with the C++ backend,
this API allows C++ programmers to train networks in C++.
+* [Gluon Python Interface](../gluon/index.html) - train complex models
imperatively and then deploy with a symbolic graph.
+* [Julia API](../api/julia/index.html) *(Community Supported)* - train models
with multiple GPUs using Julia.
+* [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.
+* [MinPy](https://github.com/dmlc/minpy) - Pure numpy practice with third
party operator integration and MXNet as backend for GPU computing
+* [Module Python API](../api/python/index.html) - backed by the Symbol API,
you can define your network in a declarative fashion.
+* [ONNX-MXnet API](../api/python/contrib/onnx.html) - train and use Open
Neural Network eXchange (ONNX) model files.
+* [Perl API](../api/perl/index.html) *(Community Supported)* - train models
with multiple GPUs using Perl.
+* [R API](https://mxnet.incubator.apache.org/api/r/index.html) *(Community
Supported)* - train models with multiple GPUs using R.
+* [Scala Infer API](../api/scala/infer.html) - model loading and inference
functionality.
+* [TensorFuse](https://github.com/dementrock/tensorfuse) - Common interface
for Theano, CGT, TensorFlow, and MXNet (experimental) by
[dementrock](https://github.com/dementrock)
+
+
+## Toolkits to Extend MXNet
+
+* [Gluon CV](https://gluon-cv.mxnet.io/) - state-of-the-art deep learning
algorithms in computer vision.
+* [Gluon NLP](https://gluon-nlp.mxnet.io/) - state-of-the-art deep learning
models in natural language processing.
+* [Sockeye](https://github.com/awslabs/sockeye) - a sequence-to-sequence
framework for Neural Machine Translation
+
+
+## Debugging and Visualization
+
+* [MXBoard](https://github.com/awslabs/mxboard) - lets you to visually inspect
and interpret your MXNet runs and graphs using the TensorBoard software.
+
+
+## Model Serving
+
+* [MXNet Model Server
(MMS)](https://github.com/apache/incubator-mxnet/tree/master/example/model-server/mms.md)
- simple yet scalable solution for model inference.
+
+
+## Model Zoos
+
+* [Gluon Model Zoo](https://github.com/awslabs/mxnet-model-server) - models
trained in Gluon and available through Gluon's model zoo API.
+* [ONNX Model Zoo](https://github.com/onnx/models) - 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](contribute.html),
and browse the [design
proposals](https://cwiki.apache.org/confluence/display/MXNET/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](https://mxnet.incubator.apache.org/community/contribute.html#mxnet-dev-communications)
if you would like to know more, or [create a GitHub
issue](https://github.com/apache/incubator-mxnet/issues/new) if you would like
to propose something for the MXNet ecosystem.
diff --git a/example/README.md b/example/README.md
index 0dc6138c2ef..8d91e7c1a0f 100644
--- a/example/README.md
+++ b/example/README.md
@@ -22,10 +22,12 @@ This page contains a curated list of awesome MXNet
examples, tutorials and blogs
If you want to contribute to this list and the examples, please open a new
pull request.
+
### Examples
Example applications or scripts should be submitted in this `example` folder.
+
### Tutorials
If you have a tutorial idea for the website, download the [Jupyter notebook
tutorial
template](https://github.com/dmlc/mxnet/tree/master/example/MXNetTutorialTemplate.ipynb).
@@ -155,6 +157,7 @@ If your tutorial depends on specific packages, simply add
them to this provision
* [Deformable ConvNets](https://arxiv.org/abs/1703.06211)
([github](https://github.com/msracver/Deformable-ConvNets)) by
[MSRACVer](https://github.com/msracver)
* [OCR with bi-LSTM and CTC Loss in
Gluon](https://github.com/ThomasDelteil/Gluon_OCR_LSTM_CTC) by
[ThomasDelteil](https://github.com/ThomasDelteil)
* [Visual Search with Gluon and
HNSWlib](https://github.com/ThomasDelteil/VisualSearch_MXNet), by
[ThomasDelteil](https://github.com/ThomasDelteil), online demo
[here](https://thomasdelteil.github.io/VisualSearch_MXNet/)
+* [MXNet-face](https://github.com/tornadomeet/mxnet-face) - Using MXNet for a
face-related algorithm by [tornadomeet](https://github.com/tornadomeet) where
the single model gets 97.13%+-0.88% accuracy on LFW, and with only 20MB size
### <a name="ipython-notebooks"></a>IPython Notebooks
-----------------
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