About: OpenNN is an open source class library written in C++ which implements neural networks. The library has been designed to learn from both data sets and mathematical models. Changes:Initial Announcement on mloss.org.

About: A Tool for Embedding Strings in Vector Spaces Changes:Fixed severe bug in concurrent computation of blended ngrams.

About: A Tool for Measuring String Similarity Changes:Several minor bugfixes.

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly nonlinear and nonconvex functions, using the CMAES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability. Changes:This is an important update:

About: LuaMapReduce framework implemented in Lua using luamongo driver and MongoDB as storage. It follows Iterative MapReduce for training of Machine Learning statistical models. Changes:

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 contains mostly minor bug fixes and usability improvements, with the notable exception of new routines for extracting localbinarypattern features from images and improved tools for learning distance metrics.

About: Hubnessaware Machine Learning for Highdimensional Data Changes:Initial Announcement on mloss.org.

About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use, with a function syntax similar to MATLAB. Matrix decompositions are provided through optional integration with LAPACK, or one of its high performance dropin replacements (eg. Intel MKL, OpenBLAS). Changes:

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more. Changes:Initial Announcement on mloss.org.

About: LogRegCrowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979). Changes:Initial Announcement on mloss.org.

About: This library implements the OptimumPath Forest classifier for unsupervised and supervised learning. Changes:Initial Announcement on mloss.org.

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over datadependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. Changes:improved testing, improved documentation, windows compatibility, more algorithms

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinearoptimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python. Changes:Fixed bugs and doc typos

About: Multicore nonparametric and bursty topic models (HDPLDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls. Changes:Corrections to diagnostics and topic report. Correction to estimating alpha. Now estimating beta sometimes (when estimating phi).

About: Somoclu is a massively parallel implementation of selforganizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Changes:

About: A platformindependent C++ framework for machine learning, graphical models, and computer vision research and development. Changes:Version 1.8:

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. Changes:New features:  R support that is now on CRAN

About: A Content Anomaly Detector based on nGrams Changes:Lots and lots of cool new features and bugfixes ;)

About: The implementation of adaptive probabilistic mappings. Changes:Initial Announcement on mloss.org.

About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; Oneshot training for an entire regularization path; Continuous checkpointing; much more Changes:
