About: Variational Bayesian inference tools for Python Changes:

About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of stateoftheart deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on nonGPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode). Changes:LOTS of stuff: https://github.com/BVLC/caffe/releases/tag/v0.9999

About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as crossvalidation and a plethora of score functions. Changes:Initial Announcement on mloss.org.

About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning. Changes:Changelog pyGPs v1.2June 30th 2014structural updates:
bug fixes:
July 8th 2014structural updates:
bug fixes:
July 14th 2014documentation updates:
structural updates:

About: Crino: a neuralnetwork library based on Theano Changes:1.0.0 (7 july 2014) :  Initial release of crino  Implements a torchlike library to build artificial neural networks (ANN)  Provides standard implementations for : * autoencoders * multilayer perceptrons (MLP) * deep neural networks (DNN) * input output deep architecture (IODA)  Provides a batchgradient backpropagation algorithm, with adaptative learning rate

About: ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories. Changes:Initial Announcement on mloss.org.

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the wellknown SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation. Changes:Initial Announcement on mloss.org.

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:Added MI criterion Simplified Python install Fixed bugs in annealed criteria

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:

About: This project is a C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems. Changes:Fixed a bug in the way file serialization was being handled on MS Windows platforms.

About: Universal Pythonwritten numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies Changes:http://openopt.org/Changelog

About: eXtreme gradient boosting (tree) library. Features:  Sparse feature format allows easy handling of missing values, and improve computation efficiency.  Efficient parallel implementation that optimizes memory and computation.  Python interface Changes:New features:  Python interface  New objectives: weighted training, pairwise rank, multiclass softmax  Comes with example script on Kaggle Higgs competition, 20 times faster than skilearn's GBRT

About: peewit provides services for programming, running and result examination of machine learning experiments. It does not include any ML algorithms, has no GUI, and presumes certain uniformity of the experimental layout. But it does not make assumptions on the type of task under study. The current versionnumber is 0.10. Changes:vcube with sidecubes

About: C++ software for statistical classification, probability estimation and interpolation/nonlinear regression using variable bandwidth kernel estimation. Changes:New in Version 0.9.7:

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: Scalable tensor factorization 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 0.6 (December 3th, 2013) Highlight:
0.6rc4 skipped for a technical reason. Highlights (since 0.6rc3):
Too much changes in 0.6rc1, 0.6rc2 and 0.6rc3 to list here. See https://github.com/Theano/Theano/blob/master/NEWS.txt for details.

About: Jubatus is a general framework library for online and distributed machine learning. It currently supports classification, regression, clustering, recommendation, nearest neighbors, anomaly detection, and graph analysis. Loose model sharing provides higher scalability, better performance, and realtime capabilities, by combining online learning with distributed computations. Changes:0.5.0 add new supports for clustering and nearest neighbors. For more detail, see http://t.co/flMcTcYZVs

About: Bob is a free signalprocessing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland. Changes:Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics: Diff URL: https://github.com/idiap/bob/compare/v1.1.4...HEAD Commits: 629 Files changed: 954 Contributors: 7 Here is a quick list of things you should pay attention for while integrating your satellite packages against Bob 1.2.x:
For a detailed list of changes and additions, please look at our Changelog page for this release and minor updates: https://github.com/idiap/bob/wiki/Changelogfrom1.1.4to1.2 https://github.com/idiap/bob/wiki/Changelogfrom1.2.0to1.2.1 https://github.com/idiap/bob/wiki/Changelogfrom1.2.1to1.2.2

About: Embarrassingly Parallel Array Computing: EPAC is a machine learning workflow builder. Changes:Initial Announcement on mloss.org.
