view doc/index.txt @ 1415:234e5e48d60d

added datasets.tinyimages.rebuild_numpy_file method to build 5GB memmappable file of all images
author James Bergstra <bergstrj@iro.umontreal.ca>
date Thu, 03 Feb 2011 18:07:04 -0500
parents 9ce32a8252d2
children 04d859714506
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Welcome
=======

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::

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

The ``pylearn`` subfolder should be on your ``$PYTHONPATH``.

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.