Mercurial > pylearn
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> |
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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.