https://pypi.org/project/mdp/ Recent updates to the Python Package Index for MDP en https://pypi.org/project/mdp/3.6/ MDP is a Python library for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. mdp-toolkit@python.org Fri, 24 Apr 2020 20:29:33 GMT https://pypi.org/project/mdp/3.5/ MDP is a Python library for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. mdp-toolkit-devel@lists.sourceforge.net Tue, 08 Mar 2016 13:01:12 GMT https://pypi.org/project/mdp/3.4/ MDP is a Python library for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. mdp-toolkit-devel@lists.sourceforge.net Fri, 04 Mar 2016 11:17:29 GMT https://pypi.org/project/mdp/3.3/ MDP is a Python library for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. mdp-toolkit-devel@lists.sourceforge.net Thu, 04 Oct 2012 13:16:19 GMT https://pypi.org/project/mdp/3.2/ MDP is a Python library for building complex data processing software by combining widely used machine learning algorithms into pipelines and networks. mdp-toolkit-devel@lists.sourceforge.net Mon, 24 Oct 2011 13:42:26 GMT https://pypi.org/project/mdp/3.1/ 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. mdp-toolkit-devel@lists.sourceforge.net Wed, 30 Mar 2011 17:19:49 GMT https://pypi.org/project/mdp/3.0/ 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. mdp-toolkit-devel@lists.sourceforge.net Mon, 17 Jan 2011 15:34:20 GMT https://pypi.org/project/mdp/2.6/ Modular toolkit for Data Processing (MDP) is a library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. Implemented algorithms include Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), and many more. berkes@brandeis.edu, rike.schuppner@bccn-berlin.de, mail@nikowilbert.de, tiziano.zito@bccn-berlin.de Fri, 14 May 2010 17:19:17 GMT https://pypi.org/project/mdp/2.5/ Modular toolkit for Data Processing (MDP) is a library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. Implemented algorithms include Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), and many more. berkes@brandeis.edu, mail@nikowilbert.de, tiziano.zito@bccn-berlin.de Tue, 30 Jun 2009 12:55:27 GMT https://pypi.org/project/mdp/2.4/ Modular toolkit for Data Processing (MDP) is a library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. Implemented algorithms include Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), and many more. berkes@brandeis.edu, mail@nikowilbert.de, tiziano.zito@bccn-berlin.de Wed, 22 Oct 2008 09:08:32 GMT https://pypi.org/project/mdp/2.3/ Modular toolkit for Data Processing (MDP) is a Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), Gaussian Classifiers, Restricted Boltzmann Machines, and many more. berkes@gatsby.ucl.ac.uk, mail@nikowilbert.de, tiziano.zito@bccn-berlin.de Thu, 15 May 2008 18:08:22 GMT https://pypi.org/project/mdp/2.1/ MDP is a Python data processing framework. Implemented algorithms include: Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis, Independent Slow Feature Analysis, and many more. berkes@gatsby.ucl.ac.uk, t.zito@biologie.hu-berlin.de Fri, 23 Mar 2007 19:34:37 GMT https://pypi.org/project/mdp/2.0RC/ MDP is a Python data processing framework. Implemented algorithms include: Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis, Growing Neural Gas, Factor Analysis, Fisher Discriminant Analysis, and Gaussian Classifiers. berkes@gatsby.ucl.ac.uk, t.zito@biologie.hu-berlin.de Fri, 30 Jun 2006 13:11:23 GMT https://pypi.org/project/mdp/1.1.0/ Modular toolkit for Data Processing (MDP) is a Python library to perform data processing. Already implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), and Growing Neural Gas (GNG). Mon, 13 Jun 2005 13:12:01 GMT