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 upgrades dlib's CNN+MMOD object detector to support creating multiclass detectors. It also includes significant speed improvements, allowing the detector to run at 98fps when executed on a NVIDIA 1080ti GPU. This release also adds a new 5 point face landmarking model that is over 10x smaller than the 68 point model, runs faster, and works with both HOG and CNN generated face detections. It is now the recommended landmarking model to use for face alignment.

About: Code for Calibrated AdaMEC for binary costsensitive classification. The method is just AdaBoost that properly calibrates its probability estimates and uses a costsensitive (i.e. riskminimizing) decision threshold to classify new data. Changes:Updated license information

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

About: A Content Anomaly Detector based on nGrams Changes:A teeny tiny fix to correctly handle input strings shorter than a registers width

About: A Tool for Measuring String Similarity Changes:This release fixes the incorrect implementation of the bag distance.

About: A Python based library for running experiments with Deep Learning and Ensembles on GPUs. Changes:Initial Announcement on mloss.org.

About: APRILANN toolkit (A Pattern Recognizer In Lua with Artificial Neural Networks). This toolkit incorporates ANN algorithms (as dropout, stacked denoising autoencoders, convolutional neural networks), with other pattern recognition methods as hidden makov models (HMMs) among others. Changes:
C/C++

About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more Changes:This version comes with Distributed and Mobile Examples

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: Learning MWay Tree  Web Scale Clustering  EMtree, Ktree, kmeans, TSVQ, repeated kmeans, clustering, random projections, random indexing, hashing, bit signatures Changes:Initial Announcement on mloss.org.

About: A Tool for Embedding Strings in Vector Spaces Changes:Support for explicit selection of granularity added. Several minor bug fixes. We have reached 1.0

About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line. Changes:This release features the work of our 8 GSoC 2014 students [student; mentors]:
It also contains several cleanups and bugfixes: Features
Bugfixes
Cleanup and API Changes

About: C++ software for statistical classification, probability estimation and interpolation/nonlinear regression using variable bandwidth kernel estimation. Changes:New in Version 0.9.8:

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

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications. Changes:

About: DRVQ is a C++ library implementation of dimensionalityrecursive vector quantization, a fast vector quantization method in highdimensional Euclidean spaces under arbitrary data distributions. It is an approximation of kmeans that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a byproduct of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. Changes:Initial Announcement on mloss.org.

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: Software to perform isoline retrieval, retrieve isolines of an atmospheric parameter from a nadirlooking satellite. Changes:Added screenshot, keywords

About: A work in progress Changes:Initial Announcement on mloss.org.
