Modular toolkit for Data Processing 2.5 released

We are glad to announce release 2.5 of the Modular toolkit for Data
Processing (MDP).

MDP is a Python library of widely used data processing algorithms that
can be combined according to a pipeline analogy to build more complex
data processing software. The base of available algorithms includes,
to name but the most common, Principal Component Analysis (PCA and
NIPALS), several Independent Component Analysis algorithms (CuBICA,
FastICA, TDSEP, JADE, and XSFA), Slow Feature Analysis, Restricted Boltzmann
Machine, and Locally Linear Embedding.

What's new in version 2.5?
--------------------------------------

- New nodes for XSFA, Linear Regression, Histogram, Cutoffs 

- The parallel package has grown more features
 
- Tons of bug fixes

Resources
---------
Download: http://sourceforge.net/project/showfiles.php?group_id=116959
Homepage: http://mdp-toolkit.sourceforge.net
Mailing list: http://sourceforge.net/mail/?group_id=116959

--

Pietro Berkes
Volen Center for Complex Systems
Brandeis University
Waltham, MA, USA

Niko Wilbert
Institute for Theoretical Biology
Humboldt-University
Berlin, Germany

Tiziano Zito
Bernstein Center for Computational Neuroscience
Humboldt-University
Berlin, Germany

-- 
http://mail.python.org/mailman/listinfo/python-announce-list

        Support the Python Software Foundation:
        http://www.python.org/psf/donations/