

MLPY - high-performance Python library for predictive modeling - helwr
https://mlpy.fbk.eu/

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bravura
I'm not aware of anyone who uses mlpy, but I would be curious to hear about
experiences with it.

In Python, for general Machine Learning I really like scikits.learn
(<http://scikit-learn.sourceforge.net/>). The library is Pythonic and includes
many common ML tools I need.

I have heard good things about Shogun (<http://www.shogun-toolbox.org/>),
which is written in C++ and has bindings for many other languages, including
Python. Shogun appears to be more focused on kernel algorithms (e.g. SVMs).

There's a GSOC project to bind Vowpal Wabbit in Shogun. That would be sweet.
This was mentioned by John Langford on the VW mailing list.

Theano (<http://deeplearning.net/software/theano/>) is great if you are
devising your own ML models, particularly ones that are based upon gradient
descent. It's Python and it automatically compiles to C/C++ and then machine
code for your CPU or GPU.

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coop11
I agree about scikits.learn. Olivier Grisel did a great job introducing it at
Pycon and I find that the documentation makes it more inviting for those new
to machine learning.

~~~
ogrisel
Thanks for the feedback :)

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daemon
Previous, related discussion: <http://news.ycombinator.com/item?id=490851>

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sebkomianos
A good chance to teach both Machine Learning and Python, should be interesting
to see if any lecturers actually try it..

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kqueue
On a related note

<http://academicearth.org/courses/machine-learning>

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egypturnash
My Little PonY?

