MXNet Examples

This page contains a curated list of awesome MXNet examples, tutorials and blogs. It is inspired by awesome-php and awesome-machine-learning. See also Awesome-MXNet for a similar list.

Contributing
List of examples
List of tutorials
Machine Learning Challenge Winning Solutions
Tools with MXnet

<a name="Contributing"></a>Contributing

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.

Tutorial location

Notebook tutorials should be submitted in the docs/tutorials folder, so that they maybe rendered in the web site's tutorial section.

Do not forget to udpdate the docs/tutorials/index.md for your tutorial to show up on the website.

Tutorial formatting

The site expects the format to be markdown, so export your notebook as a .md via the Jupyter web interface menu (File > Download As > Markdown). Then, to enable the download notebook button in the web site's UI (example), add the following as the last line of the file (example):

<!-- INSERT SOURCE DOWNLOAD BUTTONS -->

If you want some lines to show-up in the markdown but not in the generated notebooks, add this comment  after your ![png](img_url). Like this:

![png](img_url.png)<!--notebook-skip-line-->

Typically when you have a plt.imshow() you want the image tag [png](img.png) in the .md but not in the downloaded notebook as the user will re-generate the plot at run-time.

Tutorial tests

As part of making sure all our tutorials are running correctly with the latest version of MXNet, each tutorial is run automatically through a python2 and python3 jupyter notebook kernel in the CI, in a GPU environment, checking for errors and warnings.

Add your own test here tests/tutorials/test_tutorials.py. (If you forget, don't worry your PR will not pass the sanity check).

If your tutorial depends on specific packages, simply add them to this provisioning script: ci/docker/install/ubuntu_tutorials.sh

<a name="list-of-examples"></a>List of examples

<a name="language-binding-examples"></a>Languages Binding Examples

MXNet C++ API
- C++ examples - Example code for using C++ interface, including NDArray, symbolic layer and models.
MXNet Python API
MXNet Java API
MXNet Scala API
MXNet R API
MXNet Julia API
MXNet Perl API
go-mxnet-predictor - Go binding for inference
MXNet Javascript - MXNetJS: Javascript Package for Deep Learning in Browser (without server)

<a name="deep-learning-examples-mxnet"></a>Deep Learning Examples in the MXNet Project Repository

Autoencoder - unsupervised feature learning
Gluon Examples - several examples using the Gluon API
- Style Transfer - a style transfer example using gluon
- Word Language Model - an example that trains a multi-layer RNN on the Penn Treebank language modeling benchmark
- SN-GAN - an example that utilizes spectral normalization to train GAN(Generative adversarial network) using Gluon API
Image Classification with R - image classification on MNIST,CIFAR,ImageNet-1k,ImageNet-Full, with multiple GPU and distributed training.
Kaggle 2nd national data science bowl - a tutorial for Kaggle Second Nation Data Science Bowl
Multi-task Learning - how to use MXNet for multi-task learning
Profiling - generate profiling results in json files
Quantization and Calibration Examples - examples of quantizing a FP32 model to INT8 and performing low-precision inference with oneDNN on CPU or cuDNN on GPU
Recommender Systems - examples of how to build various kinds of recommender systems
Restricted Boltzmann Machine - an example of the binary restricted Boltzmann machine learning MNIST
Single Shot MultiBox Detector - SSD object recognition example

<a name="deep-learning-examples-other"></a>Other Deep Learning Examples with MXNet

Face Recognition with ArcFace - ONNX model for face recognition with notebooks for training, validating and running inference in MXNet by abhinavs95
Chinese plate recognition - Recognize Chinese vehicle plate, by imistyrain
Fast R-CNN by Jian Guo
"End2End Captcha Recognition (OCR)" by xlvector github link Blog in Chinese
"Prediction step of xlvector's lstm ocr" by melody-rain github link Blog in Chinese
"Solving classification + regression with MXnet in Multi Input + Multi Obj" by xlvector github link Blog in Chinese
"Learn to sort by LSTM" by xlvector github link Blog in Chinese
Neural Art using extremely lightweight (<500K) neural network Lightweight version of mxnet neural art implementation by Pavel Gonchar
Neural Art with generative networks by zhaw
Faster R-CNN in MXNet with distributed implementation and data parallelization
Asynchronous Methods for Deep Reinforcement Learning in MXNet by zmonoid
Deep Q-learning in MXNet by zmonoid
Face Detection with End-to-End Integration of a ConvNet and a 3D Model (ECCV16) by tfwu, source code for paper Yunzhu Li, Benyuan Sun, Tianfu Wu and Yizhou Wang, "Face Detection with End-to-End Integration of a ConvNet and a 3D Model", ECCV 2016 https://arxiv.org/abs/1606.00850
End-to-End Chinese plate recognition base on MXNet by szad670401
Reproduce ResNet-v2 (Identity Mappings in Deep Residual Networks) using MXNet by tornadomeet
Learning similarity among images in MXNet by xlvector in Chinese. Github link
Matrix decomposition (SVD) with MXNet by xlvector in Chinese. Github link
MultiGPU enabled image generative models (GAN and DCGAN) by Tianqi Chen
Deep reinforcement learning for playing flappybird by mxnet by LIHaoran
Neural Style in Markov Random Field (MRF) and Perceptual Losses Realtime transfer by zhaw
MTCNN Face keypoints detection and alignment by yuanyang, source code for paper "Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks", Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li and Yu Qiao, IEEE Signal Processing Letters, 23(10), 2016
SSD: Single Shot MultiBox Object Detector by zhreshold
Fast Neural Style in Scala by Ldpe2G
LSTM Human Activity Recognition by Ldpe2G
Visual Question Answering by liuzhi136
Deformable ConvNets (github) by MSRACVer
OCR with bi-LSTM and CTC Loss in Gluon by ThomasDelteil
Visual Search with Gluon and HNSWlib, by ThomasDelteil, online demo here
MXNet-face - Using MXNet for a face-related algorithm by 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

Predict with Pre-trained model - Notebook on how to predict with pretrained model.
composite symbol - A demo of how to composite a symbolic Inception-BatchNorm Network
cifar-10 recipe - A step by step demo of how to use MXNet
cifar-100 - A demo of how to train a 75.68% accuracy CIFAR-100 model
simple bind - A demo of low level training API.
Multi task tutorial - A demo of how to train and predict multi-task network on both MNIST and your own dataset.
class active maps - A demo of how to localize the discriminative regions in an image using global average pooling (GAP) in CNNs.
DMLC MXNet Notebooks DMLC's repo for various notebooks ranging from basic usages of MXNet to state-of-the-art deep learning applications.
AWS Seoul Summit 2017 Demos The demo codes and ipython notebooks in AWS Seoul Summit 2017.
Character-level CNN for text classification Performing category classification on Amazon reviews using Gluon and character-level Convolutional Neural Networks. Online demo here

<a name="mobile-apps-examples"></a>Mobile App Examples

MXNet Android Classification App - Image classification on Android with MXNet.
MXNet iOS Classification App - Image classification on iOS with MXNet.
Compile MXnet on Xcode (in Chinese) - a step-by-step tutorial of compiling MXnet on Xcode for iOS app

<a name="web-predictive-services"></a>Web Predictive Services

MXNet Shinny - Source code for quickly creating a Shiny R app to host online image classification.
Machine Eye - Web service for local image file/image URL classification without uploading.

<a name="list-of-tutorials"></a>List of tutorials

<a name="gtc2016-hands-on"></a>GPU Technology Conference 2016 Hands-on session

<a name="deep-learning-for-hackers"></a>Deep learning for hackers with MXNet

Deep learning for hackers with MXNet (1) GPU installation and MNIST English Chinese - a tutorial of installing MXnet with GPU and introduction to deep learning by MNIST example.
Deep learning for hackers with MXNet (2): Neural art English Chinese - a tutorial of generating Van Gogh style cat paintings.

<a name="mxnet-aws"></a>MXNet on the cloud

Setup Amazon AWS GPU instance with MXnet - AWS GPU instance setup with GPU (CUDA with latest cuDNN and S3 support)
Intro Guide to AWS (MXNet with Julia) - A step-by-step guide of using spot instances with Amazon Web Services (AWS) to help you save money when training DSB models on MXNet by Mike Kim
Building Deep Neural Networks in the Cloud with Azure GPU VMs, MXNet and Microsoft R Server by Cortana Intelligence and ML Blog Team at Microsoft
Applying Deep Learning at Cloud Scale, with Microsoft R Server & Azure Data Lake by Cortana Intelligence and ML Blog Team at Microsoft
Training Deep Neural Neural Networks on ImageNet Using Microsoft R Server and Azure GPU VMs by Cortana Intelligence and ML Blog Team at Microsoft
Cloud-Scale Text Classification with Convolutional Neural Networks on Microsoft Azure by Cortana Intelligence and ML Blog Team at Microsoft
Distributed Deep Learning Made Easy at AWS/Amazon for deploying deep learning clusters using MXNet

<a name="kaggle-tutorials"></a>Kaggle tutorials

Kaggle 2nd Annual Data Science Bowl End-to-End Deep Learning Tutorial (Python) - an end-to-end python tutorial for Kaggle heart disease diagnose competition (public leaderboard score 0.0392)
Kaggle 2nd Annual Data Science Bowl End-to-End Deep Learning Tutorial (R) - an end-to-end R tutorial for Kaggle heart disease diagnose competition
Dogs vs. Cats classification with mxnet and R - end-to-end (not winning) tutorial with an example of fine-tuning in R

<a name="learning-note"></a>Learning Note

Learning Note in Chinese - MXNet learning note in Chinese.
Getting Started with MXNet by indico.io (Chinese Translation MXNet实践 by 侠天 )
{mxnet} R package from MXnet, an intuitive Deep Learning framework including CNN & RNN by TJO
MXnet with R: combined power of deep learning in Chinese by Tong He
Understand MXNet dependency engine in Chinese by Yu Yang

<a name="winning-solutions"></a>Machine Learning Challenge Winning Solutions

Dmitrii Tsybulevskii, 1st place of the Yelp Restaurant Photo Classification. Link to the Kaggle interview.

<a name="tools-with-mxnet"></a>Tools with MXnet

TensorFuse - Common interface for Theano, CGT, TensorFlow, and mxnet (experimental) by dementrock
MXnet-face - Using mxnet for face-related algorithm by tornadomeet where the single model get 97.13%+-0.88% accuracy on LFW, and with only 20MB size.
MinPy - Pure numpy practice with third party operator Integration and MXnet as backend for GPU computing
MXNet Model Server - a flexible and easy to use tool for serving Deep Learning models