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  1. adversary/
  2. autoencoder/
  3. autograd/
  4. bayesian-methods/
  5. bi-lstm-sort/
  6. caffe/
  7. captcha/
  8. cnn_text_classification/
  9. dec/
  10. fcn-xs/
  11. gan/
  12. image-classification/
  13. kaggle-ndsb1/
  14. kaggle-ndsb2/
  15. memcost/
  16. model-parallel-lstm/
  17. module/
  18. multi-task/
  19. nce-loss/
  20. neural-style/
  21. notebooks/
  22. numpy-ops/
  23. profiler/
  24. python-howto/
  25. rcnn/
  26. recommenders/
  27. reinforcement-learning/
  28. rnn/
  29. rnn-time-major/
  30. speech-demo/
  31. speech_recognition/
  32. ssd/
  33. stochastic-depth/
  34. svm_mnist/
  35. torch/
  36. utils/
  37. warpctc/
  38. MXNetTutorialTemplate.ipynb
  39. README.md
example/README.md

Awesome MXNet

This page contains a curated list of awesome MXnet examples, tutorials and blogs. It is inspired by awesome-php and awesome-machine-learning.

Contributing

If you want to contribute to this list and the examples, please open a new pull request. To get started, download the tutorial template.

List of examples

Languages Binding Examples


Deep Learning Examples


IPython Notebooks


Mobile App Examples


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.

List of tutorials

GPU Technology Conference 2016 Hands-on session

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.

MXNet on the cloud

Kaggle tutorials

Learning Note

Machine Learning Challenge Winning Solutions

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