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scikit-learn is a Python module integrating various machine learning algorithms under a common interface. It offers a wide range of methods such as Support Vector Machines, linear models (L1, L2 penalized), logistic regression, gaussian mixture models and more. The large number of algorithms aleady ... [More] implemented allows for easy comparison of accuracy and performance of various algorithms. [Less]

The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and kernel implementations, includes LinAdd optimizations and also Multiple Kernel Learning algorithms. ... [More] SHOGUN also implements a number of linear methods. It allows the input feature-objects to be dense, sparse or strings and of type int/short/double/char. It provides efficient implementations several kernels but also linear methods, hidden markov models etc. and interfaces to matlab,octave,python,R and has a cmdline interface and allows C++ extensions via a library. [Less]

PyBrain is a modular Machine Learning Library for Python. It's goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms. PyBrain is short for Python-Based Reinforcement Learning ... [More] , Artificial Intelligence and Neural Network Library. It's the Swiss army knife for machine learning and neural networking. [Less]