Welcome
=======

This library is **outdated**. We are working on new stuff currently in pylearn here: https://github.com/lisa-lab/pylearn/

Pylearn is a Python library for machine learning, built on top of Theano, our 
library for defining, optimizing and evaluating mathematical expressions
involving multi-dimensional arrays.

This documentation is under construction, but you can already access the
automatically-generated API doc, along with more extensive explanations for 
some modules.

Download
========

We recommend the latest development version, available via::

.. code-block:: bash

    hg clone http://hg.assembla.com/pylearn Pylearn

The ``Pylearn/pylearn`` subfolder contains the Python package and must
be made available to Python programs, for instance by adding the ``Pylearn``
root folder to your ``PYTHONPATH`` environment varialble:

.. code-block:: bash

    export PYTHONPATH=$PYTHONPATH:/path/to/Pylearn

Assembla project: https://www.assembla.com/spaces/pylearn/

Documentation
=============

For the moment, the following documentation is available.

* `Formulas <formulas.html>`_ -- Built-in math formulas optimized for speed and robustness
* :doc:`io.SeriesTables module <seriestables>` -- Saves error series and other statistics during training
* `API <api/>`_ -- The automatically-generated API documentation
* `V2 planning <v2_planning/index.html>`_ -- Some documentation about the planning of our next version of pylearn.

You can download the latest `PDF documentation <http://deeplearning.net/software/pylearn/pylearn.pdf>`_, rather than reading it online.