ANN: MDP 2.3 released!

[Tiziano Zito]

Dear Pythonistas, 
we are proud to announce release 2.3 of the Modular toolkit for Data Processing
(MDP): a Python data processing framework. The base of readily available
algorithms includes Principal Component Analysis (PCA and NIPALS), four flavors
of Independent Component Analysis (CuBICA, FastICA, TDSEP, and JADE), Slow
Feature Analysis, Independent Slow Feature Analysis, Gaussian Classifiers,
Growing Neural Gas, Fisher Discriminant Analysis, Factor Analysis, Restricted
Boltzmann Machine, and many more. 


What's new in version 2.3?
--------------------------

- Enhanced PCA nodes (with SVD, automatic dimensionality reduction, and
  iterative algorithms).
- A complete implementation of the FastICA algorithm.
- JADE and TDSEP nodes for more fun with ICA.
- Restricted Boltzmann Machine nodes.
- The new subpackage "hinet" allows combining nodes in arbitrary feed-forward
  network architectures with a HTML visualization tool.
- The tutorial has been updated with a section on hierarchical networks.
- MDP integrated into the official Debian repository as "python-mdp".
- A bunch 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
 Gatsby Computational Neuroscience Unit
 UCL
 London, United Kingdom
 
 Niko Wilbert
 Institute for Theoretical Biology
 Humboldt-University
 Berlin, Germany

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