# Flexible and Efficient Library for Deep Learning

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### Flexible

Supports both imperative and symbolic programmings.

### Portable

Runs on CPUs or GPUs, on clusters, servers, destkops, or mobile phones

### Multiple Lanuages

Supports over 7 programming languages, including C++, Python, R, Scala, Julia, Matlab, and Javascripts.

### Auto-Differentiation

Calculates the gradient automatically for training a model.

### Distributed on Cloud

Supports distributed training on multiple CPU/GPU machines, including AWS, GCE, Azure, and Yarn clusters.

### Performance

The well-optimized C++ backend engine parallelize both I/O and computations

MXNet is developed by collaborators from multiple universities and companies. We sincerely thank the following organizations for supporing MXNet and sponsoring its major developers (alphabetical order).