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.. topic:: Easy-to-use and general-purpose machine learning in Python

    ``scikits.learn`` is a Python module integrating classic machine
    learning algorithms in the tightly-knit world of scientific Python
    packages (`numpy <http://www.scipy.org>`_, `scipy
    <http://www.scipy.org>`_, `matplotlib
    <http://matplotlib.sourceforge.net/>`_).
    
    It aims to provide simple and efficient solutions to learning
    problems that are accessible to everybody and reusable in various
    contexts: **machine-learning as a versatile tool for science and
    engineering**.
    


:Features:
  * **Solid**: :ref:`supervised-learning`: :ref:`svm`, :ref:`linear_model`.

  * **Work in progress**: :ref:`unsupervised-learning`:
    :ref:`clustering`, :ref:`mixture`, manifold learning, :ref:`ICA
    <ICA>`, :ref:`gaussian_process`

  * **Planed**: Gaussian graphical models, matrix factorization

:License:
  Open source, commercially usable: **BSD license** (3 clause)


.. include:: includes/big_toc_css.rst

.. note:: This document describes scikits.learn |release|. For other
   versions and printable format, see :ref:`documentation_resources`.

User Guide
==========

.. toctree::
   :maxdepth: 2

   contents

Example Gallery
===============

.. toctree::
   :maxdepth: 2

   auto_examples/index


Development
===========
.. toctree::
   :maxdepth: 2

   developers/index
   developers/performance
   about