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