Keras 1.2.2 with MXNet Backend  

Highlights

1. Adding Apache MXNet backend for Keras 1.2.2.
2. Easy to use multi-gputraining with MXNet backend.
3. High-performance model training in Keras with MXNet backend.

Getting Started Resources

1. Installation - https://github.com/dmlc/keras/wiki/Installation
2. How to use Multi-GPU for training in Keras with MXNet backend - https://github.com/dmlc/keras/wiki/Using-Keras-with-MXNet-in-Multi-GPU-mode
3. For more examples explore keras/examples directory.
4. Source Repo - https://github.com/dmlc/keras

For more details on unsupported functionalities, known issues and resources referrelease refer to release notes - https://github.com/dmlc/keras/releases

Apple CoreML Converter

You can now convert your MXNet models into Apple CoreML format so that they can be run on Apple devices . So now whichmeans that you can build an your next iPhone app which uses using your own MXNet model!

We currently support conversion of models that are similar to:

• Inception
• Network-In-Network
• Squeezenet
• Resnet
• Vgg
• <More coming soon>

List of layers that can be currently converted: Activation, Batchnorm, Concat, Convolution, Deconvolution, Dense, Elementwise, Flatten, Pooling, Reshape, Softmax, Transpose. <More coming soon>.