A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php. Other awesome lists can be found in the awesome-awesomeness list.

If you want to contribute to this list (please do), send me a pull request or contact me @josephmisiti

For a list of free machine learning books available for download, go 

here

Table of Contents

C

General-Purpose Machine Learning

• Recommender - A C library for product recommendations/suggestions using collaborative filtering (CF).
• Accord-Framework -The Accord.NET Framework is a complete framework for building machine learning, computer vision, computer audition, signal processing and statistical applications.

Computer Vision

• CCV - C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library
• VLFeat - VLFeat is an open and portable library of computer vision algorithms, which has Matlab toolbox

C++

Computer Vision

• OpenCV - OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
• DLib - DLib has C++ and Python interfaces for face detection and training general object detectors.
• EBLearn - Eblearn is an object-oriented C++ library that implements various machine learning models

General-Purpose Machine Learning

• DLib - A suite of ML tools designed to be easy to imbed in other applications
• ecogg
• shark
• Vowpal Wabbit (VW) - A fast out-of-core learning system.
• sofia-ml - Suite of fast incremental algorithms.
• Shogun - The Shogun Machine Learning Toolbox
• Caffe - A deep learning framework developed with cleanliness, readability, and speed in mind. [DEEP LEARNING]
• CXXNET - Yet another deep learning framework with less than 1000 lines core code [DEEP LEARNING]
• XGBoost - A parallelized optimized general purpose gradient boosting library.
• CUDA - This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING]
• Stan - A probabilistic programming language implementing full Bayesian statistical inference with Hamiltonian Monte Carlo sampling
• BanditLib - A simple Multi-armed Bandit library.
• Timbl - A software package/C++ library implementing several memory-based learning algorithms, among which IB1-IG, an implementation of k-nearest neighbor classification, and IGTree, a decision-tree approximation of IB1-IG. Commonly used for NLP.

Natural Language Processing

• MIT Information Extraction Toolkit - C, C++, and Python tools for named entity recognition and relation extraction
• CRF++ - Open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data & other Natural Language Processing tasks.
• BLLIP Parser - BLLIP Natural Language Parser (also known as the Charniak-Johnson parser)
• colibri-core - C++ library, command line tools, and Python binding for extracting and working with with basic linguistic constructions such as n-grams and skipgrams in a quick and memory-efficient way.
• ucto - Unicode-aware regular-expression based tokeniser for various languages. Tool and C++ library. Supports FoLiA format.
• frog - Memory-based NLP suite developed for Dutch: PoS tagger, lemmatiser, dependency parser, NER, shallow parser, morphological analyser.

Speech Recognition

• Kaldi - Kaldi is a toolkit for speech recognition written in C++ and licensed under the Apache License v2.0. Kaldi is intended for use by speech recognition researchers.

Sequence Analysis

• ToPS - This is an objected-oriented framework that facilitates the integration of probabilistic models for sequences over a user defined alphabet.

Clojure

Natural Language Processing

• Clojure-openNLP - Natural Language Processing in Clojure (opennlp)
• Infections-clj - Rails-like inflection library for Clojure and ClojureScript

General-Purpose Machine Learning

• Touchstone - Clojure A/B testing library
• Clojush - he Push programming language and the PushGP genetic programming system implemented in Clojure
• Infer - Inference and machine learning in clojure
• Clj-ML - A machine learning library for Clojure built on top of Weka and friends
• Encog - Clojure wrapper for Encog (v3) (Machine-Learning framework that specialises in neural-nets)
• Fungp - A genetic programming library for Clojure
• Statistiker - Basic Machine Learning algorithms in Clojure.
• clortex - General Machine Learning library using Numenta’s Cortical Learning Algorithm
• comportex - Functionally composable Machine Learning library using Numenta’s Cortical Learning Algorithm

Data Analysis / Data Visualization

• Incanter - Incanter is a Clojure-based, R-like platform for statistical computing and graphics.
• PigPen - Map-Reduce for Clojure.
• Envision - Clojure Data Visualisation library, based on Statistiker and D3 ## Erlang

General-Purpose Machine Learning

• Disco - Map Reduce in Erlang

Go

Natural Language Processing

• go-porterstemmer - A native Go clean room implementation of the Porter Stemming algorithm.
• paicehusk - Golang implementation of the Paice/Husk Stemming Algorithm.
• snowball - Snowball Stemmer for Go.
• go-ngram - In-memory n-gram index with compression.

General-Purpose Machine Learning

• Go Learn - Machine Learning for Go
• go-pr - Pattern recognition package in Go lang.
• bayesian - Naive Bayesian Classification for Golang.
• go-galib - Genetic Algorithms library written in Go / golang
• Cloudforest - Ensembles of decision trees in go/golang.
• gobrain - Neural Networks written in go

Data Analysis / Data Visualization

• go-graph - Graph library for Go/golang language.
• SVGo - The Go Language library for SVG generation

Haskell

General-Purpose Machine Learning

• haskell-ml - Haskell implementations of various ML algorithms.
• HLearn - a suite of libraries for interpreting machine learning models according to their algebraic structure.
• hnn - Haskell Neural Network library.
• hopfield-networks - Hopfield Networks for unsupervised learning in Haskell.

Java

Natural Language Processing

• CoreNLP - Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words
• Stanford Parser - A natural language parser is a program that works out the grammatical structure of sentences
• Stanford POS Tagger - A Part-Of-Speech Tagger (POS Tagger
• Stanford Name Entity Recognizer - Stanford NER is a Java implementation of a Named Entity Recognizer.
• Stanford Word Segmenter - Tokenization of raw text is a standard pre-processing step for many NLP tasks.
• Tregex, Tsurgeon and Semgrex - Tregex is a utility for matching patterns in trees, based on tree relationships and regular expression matches on nodes (the name is short for "tree regular expressions").
• Stanford English Tokenizer - Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java.
• Stanford Tokens Regex - A tokenizer divides text into a sequence of tokens, which roughly correspond to "words"
• Stanford Temporal Tagger - SUTime is a library for recognizing and normalizing time expressions.
• Stanford SPIED - Learning entities from unlabeled text starting with seed sets using patterns in an iterative fashion
• Stanford Topic Modeling Toolbox - Topic modeling tools to social scientists and others who wish to perform analysis on datasets
• Twitter Text Java - A Java implementation of Twitter's text processing library
• MALLET - A Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
• OpenNLP - a machine learning based toolkit for the processing of natural language text.
• LingPipe - A tool kit for processing text using computational linguistics.
• ClearTK - ClearTK provides a framework for developing statistical natural language processing (NLP) components in Java and is built on top of Apache UIMA.
• Apache cTAKES - Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) is an open-source natural language processing system for information extraction from electronic medical record clinical free-text.

General-Purpose Machine Learning

• Datumbox - Machine Learning framework for rapid development of Machine Learning and Statistical applications
• ELKI - Java toolkit for data mining. (unsupervised: clustering, outlier detection etc.)
• H2O - ML engine that supports distributed learning on data stored in HDFS.
• htm.java - General Machine Learning library using Numenta’s Cortical Learning Algorithm
• java-deeplearning - Distributed Deep Learning Platform for Java, Clojure,Scala
• JAVA-ML - A general ML library with a common interface for all algorithms in Java
• JSAT - Numerous Machine Learning algoirhtms for classification, regresion, and clustering.
• Mahout - Distributed machine learning
• Meka - An open source implementation of methods for multi-label classification and evaluation (extension to Weka).
• MLlib in Apache Spark - Distributed machine learning library in Spark
• Neuroph - Neuroph is lightweight Java neural network framework
• ORYX - Simple real-time large-scale machine learning infrastructure.
• RankLib - RankLib is a library of learning to rank algorithms
• RapidMiner - RapidMiner integration into Java code
• Stanford Classifier - A classifier is a machine learning tool that will take data items and place them into one of k classes.
• WalnutiQ - object oriented model of the human brain
• Weka - Weka is a collection of machine learning algorithms for data mining tasks

Speech Recognition

• CMU Sphinx - Open Source Toolkit For Speech Recognition purely based on Java speech recognition library.

Data Analysis / Data Visualization

• Hadoop - Hadoop/HDFS
• Spark - Spark is a fast and general engine for large-scale data processing.
• Impala - Real-time Query for Hadoop

Javascript

Natural Language Processing

• Twitter-text-js - A JavaScript implementation of Twitter's text processing library
• NLP.js - NLP utilities in javascript and coffeescript
• natural - General natural language facilities for node
• Knwl.js - A Natural Language Processor in JS
• Retext - Extensible system for analysing and manipulating natural language
• TextProcessing - Sentiment analysis, stemming and lemmatization, part-of-speech tagging and chunking, phrase extraction and named entity recognition.

Data Analysis / Data Visualization

• D3.js
• dc.js
• D3xter - Straight forward plotting built on D3
• statkit - Statistics kit for JavaScript
• science.js - Scientific and statistical computing in JavaScript.
• Z3d - Easily make interactive 3d plots built on Three.js

General-Purpose Machine Learning

• Convnet.js - ConvNetJS is a Javascript library for training Deep Learning models[DEEP LEARNING]
• Clustering.js - Clustering algorithms implemented in Javascript for Node.js and the browser
• Decision Trees - NodeJS Implementation of Decision Tree using ID3 Algorithm
• Node-fann - FANN (Fast Artificial Neural Network Library) bindings for Node.js
• Kmeans.js - Simple Javascript implementation of the k-means algorithm, for node.js and the browser
• LDA.js - LDA topic modeling for node.js
• Learning.js - Javascript implementation of logistic regression/c4.5 decision tree
• Machine Learning - Machine learning library for Node.js
• Node-SVM - Support Vector Machine for nodejs
• Brain - Neural networks in JavaScript
• Bayesian-Bandit - Bayesian bandit implementation for Node and the browser.
• Synaptic - Architecture-free neural network library for node.js and the browser
• kNear - JavaScript implementation of the k nearest neighbors algorithm for supervised learning

Julia

General-Purpose Machine Learning

• PGM - A Julia framework for probabilistic graphical models.
• DA - Julia package for Regularized Discriminant Analysis
• Regression - Algorithms for regression analysis (e.g. linear regression and logistic regression)
• Local Regression - Local regression, so smooooth!
• Naive Bayes - Simple Naive Bayes implementation in Julia
• Mixed Models - A Julia package for fitting (statistical) mixed-effects models
• Simple MCMC - basic mcmc sampler implemented in Julia
• Distance - Julia module for Distance evaluation
• Decision Tree - Decision Tree Classifier and Regressor
• Neural - A neural network in Julia
• MCMC - MCMC tools for Julia
• GLM - Generalized linear models in Julia
• GLMNet - Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet
• Clustering - Basic functions for clustering data: k-means, dp-means, etc.
• SVM - SVM's for Julia
• Kernal Density - Kernel density estimators for julia
• NMF - A Julia package for non-negative matrix factorization
• ANN - Julia artificial neural networks
• Mocha.jl - Deep Learning framework for Julia inspired by Caffe
• XGBoost.jl - eXtreme Gradient Boosting Package in Julia

Natural Language Processing

• Topic Models - TopicModels for Julia
• Text Analysis - Julia package for text analysis

Data Analysis / Data Visualization

• Graph Layout - Graph layout algorithms in pure Julia
• Data Frames Meta - Metaprogramming tools for DataFrames
• Julia Data - library for working with tabular data in Julia
• Data Read - Read files from Stata, SAS, and SPSS
• Hypothesis Tests - Hypothesis tests for Julia
• Gadfly - Crafty statistical graphics for Julia.

• Stats - Statistical tests for Julia

• RDataSets - Julia package for loading many of the data sets available in R

• DataFrames - library for working with tabular data in Julia
• Distributions - A Julia package for probability distributions and associated functions.
• Data Arrays - Data structures that allow missing values
• Time Series - Time series toolkit for Julia
• Sampling - Basic sampling algorithms for Julia

Misc Stuff / Presentations

• DSP - Digital Signal Processing (filtering, periodograms, spectrograms, window functions).
• SignalProcessing - Signal Processing tools for Julia
• Images - An image library for Julia

Lua

General-Purpose Machine Learning

• • cephes - Cephes mathematical functions library, wrapped for Torch. Provides and wraps the 180+ special mathematical functions from the Cephes mathematical library, developed by Stephen L. Moshier. It is used, among many other places, at the heart of SciPy.
  • graph - Graph package for Torch
  • randomkit - Numpy's randomkit, wrapped for Torch

  • signal - A signal processing toolbox for Torch-7. FFT, DCT, Hilbert, cepstrums, stft

  • nn - Neural Network package for Torch

  • nngraph - This package provides graphical computation for nn library in Torch7.
  • nnx - A completely unstable and experimental package that extends Torch's builtin nn library
  • optim - An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
  • unsup - A package for unsupervised learning in Torch. Provides modules that are compatible with nn (LinearPsd, ConvPsd, AutoEncoder, ...), and self-contained algorithms (k-means, PCA).
  • manifold - A package to manipulate manifolds
  • svm - Torch-SVM library
  • lbfgs - FFI Wrapper for liblbfgs
  • vowpalwabbit - An old vowpalwabbit interface to torch.
  • OpenGM - OpenGM is a C++ library for graphical modeling, and inference. The Lua bindings provide a simple way of describing graphs, from Lua, and then optimizing them with OpenGM.
  • sphagetti - Spaghetti (sparse linear) module for torch7 by @MichaelMathieu
  • LuaSHKit - A lua wrapper around the Locality sensitive hashing library SHKit
  • kernel smoothing - KNN, kernel-weighted average, local linear regression smoothers
  • cutorch - Torch CUDA Implementation
  • cunn - Torch CUDA Neural Network Implementation
  • imgraph - An image/graph library for Torch. This package provides routines to construct graphs on images, segment them, build trees out of them, and convert them back to images.
  • videograph - A video/graph library for Torch. This package provides routines to construct graphs on videos, segment them, build trees out of them, and convert them back to videos.
  • saliency - code and tools around integral images. A library for finding interest points based on fast integral histograms.
  • stitch - allows us to use hugin to stitch images and apply same stitching to a video sequence
  • sfm - A bundle adjustment/structure from motion package
  • fex - A package for feature extraction in Torch. Provides SIFT and dSIFT modules.
  • OverFeat - A state-of-the-art generic dense feature extractor
• Lunum

Demos and Scripts

• Core torch7 demos repository.
  • linear-regression, logistic-regression
  • face detector (training and detection as separate demos)
  • mst-based-segmenter
  • train-a-digit-classifier
  • train-autoencoder
  • optical flow demo
  • train-on-housenumbers
  • train-on-cifar
  • tracking with deep nets
  • kinect demo
  • filter-bank visualization
  • saliency-networks
• Music Tagging - Music Tagging scripts for torch7
• torch-datasets - Scripts to load several popular datasets including:
  • BSR 500
  • CIFAR-10
  • COIL
  • Street View House Numbers
  • MNIST
  • NORB
• Atari2600 - Scripts to generate a dataset with static frames from the Arcade Learning Environment

Matlab

Computer Vision

• Contourlets - MATLAB source code that implements the contourlet transform and its utility functions.
• Shearlets - MATLAB code for shearlet transform
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