About: A noniterative, incremental and hyperparameterfree learning method for onelayer feedforward neural networks without hidden layers. This method efficiently obtains the optimal parameters of the network, regardless of whether the data contains a greater number of samples than variables or vice versa. It does this by using a square loss function that measures errors before the output activation functions and scales them by the slope of these functions at each data point. The outcome is a system of linear equations that obtain the network's weights and that is further transformed using Singular Value Decomposition. Changes:Initial Announcement on mloss.org.

About: A noniterative learning method for onelayer (no hidden layer) neural networks, where the weights can be calculated in a closedform manner, thereby avoiding low convergence rate and also hyperparameter tuning. The proposed learning method, LANNSVD in short, presents a good computational efficiency for largescale data analytic. Changes:Initial Announcement on mloss.org.

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlablike development environment. Changes:

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. Apart from a command line interface, Python, Julia, R, and MATLAB are supported. Changes:

About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multidimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano. Changes:Theano 0.9.0 (20th of March, 2017)Highlights (since 0.8.0):

About: MSVMpack is a Multiclass Support Vector Machine (MSVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four MSVM models from the literature: Weston and Watkins MSVM, Crammer and Singer MSVM, Lee, Lin and Wahba MSVM, and the MSVM2 of Guermeur and Monfrini. Changes:

About: Armadillo is a high quality C++ linear algebra library, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products). Changes:

About: OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. The library has been designed to learn from both data sets and mathematical models. Changes:New algorithms, correction of bugs.

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features. Changes:Fixed a Windows compilation bug. MIToolbox v3 should now compile using Visual Studio.

About: The new R package opusminer provides an R interface to the OPUS Miner algorithm (implemented in C++) for finding the key associations in transaction data efficiently, in the form of selfsufficient itemsets, using either leverage or lift. Changes:Initial Announcement on mloss.org.

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 a number of new features, most notably new deep learning tools including a stateoftheart face recognition example using dlib's deep learning API. See http://dlib.net/dnn_face_recognition_ex.cpp.html for an introduction.

About: The proposed hashing algorithm leverages the bootstrap sampling idea and integrates it with PCA, resulting in a new projection method called Bagging PCA Hashing. Changes:Initial Announcement on mloss.org.

About: This is an online hashing algorithm which can handle the stream data with low computational cost. 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. Added GitHub page.

About: General purpose Java Machine Learning library for classification, regression, and clustering. Changes:See github release tab for change info

About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab. Changes:Major refactoring of FEAST to improve speed and portability.

About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...] Changes:In core weka:
In packages:

About: The scikitlearn project is a machine learning library in Python. Changes:Update for 0.18 .1

About: RLScore  regularized leastsquares machine learning algorithms package Changes:Initial Announcement on mloss.org.
