introduction.md

# Machine Learning

This section overviews machine learning frameworks and libraries available on the clusters.

## TensorFlow

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. For more information, see the [official website][a].

For the list of available versions, see the [TensorFlow][1] section:

## Theano

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation. For more information, see the [official webpage][b] (GitHub).

For the list of available versions, type:

```console
$ ml av Theano
```

## Keras

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. For more information, see the [official website][c].

For the list of available versions, type:

```console
$ ml av Keras
```

[1]: tensorflow.md

[a]: https://www.tensorflow.org/
[b]: https://github.com/Theano/
[c]: https://keras.io/