We are glad to announce release 3.3 of the Modular toolkit for Data Processing (MDP). This a bug-fix release, all current users are invited to upgrade. 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 signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others. What's new in version 3.3? -------------------------- - support sklearn versions up to 0.12 - cleanly support reload - fail gracefully if pp server does not start - several bug-fixes and improvements Resources --------- Download: http://sourceforge.net/projects/mdp-toolkit/files Homepage: http://mdp-toolkit.sourceforge.net Mailing list: http://lists.sourceforge.net/mailman/listinfo/mdp-toolkit-users Acknowledgments --------------- We thank the contributors to this release: Philip DeBoer, Yaroslav Halchenko. The MDP developers, Pietro Berkes Zbigniew Jędrzejewski-Szmek Rike-Benjamin Schuppner Niko Wilbert Tiziano Zito