About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. Changes:This release adds support for cuDNN 5.1 as well as a number of minor bug fixes and usability improvements.

About: ELKI is a framework for implementing datamining algorithms with support for index structures, that includes a wide variety of clustering and outlier detection methods. Changes:Additions and improvements from ELKI 0.7.0 to 0.7.1: Algorithm additions:
Important bug fixes:
UI improvements:
Smaller changes:

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications. Changes:

About: SALSA (Software lab for Advanced machine Learning with Stochastic Algorithms) is an implementation of the wellknown stochastic algorithms for Machine Learning developed in the highlevel technical computing language Julia. The SALSA software package is designed to address challenges in sparse linear modelling, linear and nonlinear Support Vector Machines applied to large data samples with usercentric and userfriendly emphasis. Changes:Initial Announcement on mloss.org.

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multithreading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more. Changes:Updated to version 0.3.0

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building productiongrade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details. Changes:Adding a large number of new distributions, such as AndersonDaring, ShapiroWilk, Inverse ChiSquare, Lévy, Folded Normal, Shifted LogLogistic, Kumaraswamy, Trapezoidal, Uquadratic and BetaPrime distributions, BirnbaumSaunders, Generalized Normal, Gumbel, Power Lognormal, Power Normal, Triangular, Tukey Lambda, Logistic, Hyperbolic Secant, Degenerate and General Continuous distributions. Other additions include new statistical hypothesis tests such as AndersonDaring and ShapiroWilk; as well as support for all of LIBLINEAR's support vector machine algorithms; and format reading support for MATLAB/Octave matrices, LibSVM models, sparse LibSVM data files, and many others. For a complete list of changes, please see the full release notes at the release details page at: https://github.com/accordnet/framework/releases

About: MyMediaLite is a lightweight, multipurpose library of recommender system algorithms. Changes:Mostly bug fixes. For details see: https://github.com/zenogantner/MyMediaLite/blob/master/doc/Changes

About: a dbms for resonating neural networks. Create and use different types of machine learning algorithms. Changes:AIML compatible (AIML files can be imported); new 'Grid channel' for developing board games; improved topics editor; new demo project: ALice (from AIML); lots of bugfixes and speed improvements

About: An implementation of MROGH descriptor. For more information, please refer to: “Bin Fan, Fuchao Wu and Zhanyi Hu, Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011, pp.23772384.” The most uptodate information can be found at : http://vision.ia.ac.cn/Students/bfan/index.htm Changes:Initial Announcement on mloss.org.

About: 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 preprocessing methods, and many others. Changes:What's new in version 3.3?

About: Matlab SVM toolbox for learning large margin filters in signal or images. Changes:Initial Announcement on mloss.org.

About: MATLAB toolbox for advanced BrainComputer Interface (BCI) research. Changes:Initial Announcement on mloss.org.

About: Tools for functional network analysis. Changes:Initial Announcement on mloss.org.

About: yaplf (Yet Another Python Learning Framework) is an extensible machine learning framework written in python Changes:Initial Announcement on mloss.org.

About: JavaML is a collection of machine learning and data mining algorithms, which aims to be a readily usable and easily extensible API for both software developers and research scientists. Changes:new release

About: Piqle (Platform for Implementing QLearning Experiments) is a Java framework for fast design, prototyping and test of reinforcement learning experiments (RL). By clearly separating algorithms and problems, it allows users to focus on either part of the RL paradigm:designing new algorithms or implementing new problems. Piqle implements many classical RL algorithms, making their parameters easily tunable. At this time, 13 problems are implemented, several with one or more variants. The user's manual explains in detail how to code a new problem. Written in Java, Piqle is as platformindependent as Java itself. Its components can easily be embedded as part of complex implementations, like robotics or decision making. Changes:Initial Announcement on mloss.org.

About: Aleph is both a multiplatform machine learning framework aimed at simplicity and performance, and a library of selected stateoftheart algorithms. Changes:Initial Announcement on mloss.org.

About: LaRank is an online solver for multiclass Support Vector Machines. Changes:Initial Announcement on mloss.org.

About: Nested Effects Models (NEMs) are a class of directed graphical models originally introduced to analyze the effects of gene perturbation screens with highdimensional phenotypes. In contrast to other [...] Changes:Initial Announcement on mloss.org.
