scikits.learn is a python module for machine learning built on top of scipy.
The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the AUTHORS.rst file for a complete list of contributors.
It is currently maintained by a team of volunteers.
You can download source code and Windows binaries from SourceForge:
The required dependencies to build the software are python >= 2.5, setuptools, NumPy >= 1.1, SciPy >= 0.6 (although having at least 0.7 is highly recommended and required by some modules) and a working C++ compiler.
To run the tests you will also need nose >= 0.10.
This packages uses distutils, which is the default way of installing python modules. The install command is:
python setup.py install
There's a general and development mailing list, visit https://lists.sourceforge.net/lists/listinfo/scikit-learn-general to subscribe to the mailing list.
Some developers tend to hang around the channel #scikit-learn at irc.freenode.net, especially during the week preparing a new release. If nobody is available to answer your questions there don't hesitate to ask it on the mailing list to reach a wider audience.
You can check the latest sources with the command:
git clone git://github.com/scikit-learn/scikit-learn.git
or if you have write privileges:
git clone firstname.lastname@example.org:scikit-learn/scikit-learn.git
Please submit bugs you might encounter, as well as patches and feature requests to the tracker located at github https://github.com/scikit-learn/scikit-learn/issues
After installation, you can launch the test suite from outside the source directory (you will need to have nosetest installed):
python -c "import scikits.learn as skl; skl.test()"
See web page http://scikit-learn.sourceforge.net/install.html#testing for more information.