A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php.

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

• NLTK - A leading platform for building Python programs to work with human language data.
• Pattern - A web mining module for the Python programming language. It has tools for natural language processing, machine learning, among others.
• TextBlob - Providing a consistent API for diving into common natural language processing (NLP) tasks. Stands on the giant shoulders of NLTK and Pattern, and plays nicely with both.
• jieba - Chinese Words Segmentation Utilities.
• SnowNLP - A library for processing Chinese text.
• loso - Another Chinese segmentation library.
• genius - A Chinese segment base on Conditional Random Field.

• scikit-learn - A Python module for machine learning built on top of SciPy.
• pattern - Web mining module for Python.
• NuPIC - Numenta Platform for Intelligent Computing.
• Pylearn2 - A Machine Learning library based on Theano.
• hebel - GPU-Accelerated Deep Learning Library in Python.
• gensim - Topic Modelling for Humans.
• PyBrain - Another Python Machine Learning Library.
• Crab - A flexible, fast recommender engine.
• python-recsys - A Python library for implementing a Recommender System.
• BayesPy

• SciPy - A Python-based ecosystem of open-source software for mathematics, science, and engineering.
• NumPy - A fundamental package for scientific computing with Python.
• Numba - Python JIT (just in time) complier to LLVM aimed at scientific Python by the developers of Cython and NumPy.
• NetworkX - A high-productivity software for complex networks.
• Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools.
• Open Mining - Business Intelligence (BI) in Python (Pandas web interface)
• PyMC - Markov Chain Monte Carlo sampling toolkit.
• zipline - A Pythonic algorithmic trading library.
• PyDy - Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
• SymPy - A Python library for symbolic mathematics.
• statsmodels - Statistical modeling and econometrics in Python.
• astropy - A community Python library for Astronomy.
• matplotlib - A Python 2D plotting library.
• bokeh - Interactive Web Plotting for Python.
• plotly - Collaborative web plotting for Python and matplotlib.
• vincent - A Python to Vega translator.
• d3py - A plottling library for Python, based on D3.js.
• ggplot - Same API as ggplot2 for R.
• Kartograph.py - Rendering beautiful SVG maps in Python.
• pygal - A Python SVG Charts Creator.
• pycascading

• pattern_classification
• thinking stats 2
• hyperopt
• numpic
• 2012-paper-diginorm
• ipython-notebooks
• decision-weights

• Treat - Text REtrieval and Annotation Toolkit, definitely the most comprehensive toolkit I’ve encountered so far for Ruby
• Ruby Linguistics - Linguistics is a framework for building linguistic utilities for Ruby objects in any language. It includes a generic language-independant front end, a module for mapping language codes into language names, and a module which contains various English-language utilities.
• Stemmer - Expose libstemmer_c to Ruby
• Ruby Wordnet - This library is a Ruby interface to WordNet
• Raspel - raspell is an interface binding for ruby
• UEA Stemmer - Ruby port of UEALite Stemmer - a conservative stemmer for search and indexing
• Twitter-text-rb - A library that does auto linking and extraction of usernames, lists and hashtags in tweets

• Ruby Machine Learning - Some Machine Learning algorithms, implemented in Ruby
• Machine Learning Ruby
• jRuby Mahout - JRuby Mahout is a gem that unleashes the power of Apache Mahout in the world of JRuby.
• CardMagic-Classifier - A general classifier module to allow Bayesian and other types of classifications.
• Neural Networks and Deep Learning - Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING]

• rsruby - Ruby - R bridge
• data-visualization-ruby - Source code and supporting content for my Ruby Manor presentation on Data Visualisation with Ruby
• ruby-plot - gnuplot wrapper for ruby, especially for plotting roc curves into svg files
• plot-rb - A plotting library in Ruby built on top of Vega and D3.
• scruffy - A beautiful graphing toolkit for Ruby
• SciRuby
• Glean - A data management tool for humans
• Bioruby
• Arel

• Big Data For Chimps

• Clever Algorithms For Machine Learning
• Machine Learning For Hackers

• Learning Statistics Using R

• Twitter-text-js - A JavaScript implementation of Twitter's text processing library
• NLP.js - NLP utilities in javascript and coffeescript

• High Charts
• NVD3.js
• dc.js
• chartjs
• dimple
• amCharts

• 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

• ScalaNLP - ScalaNLP is a suite of machine learning and numerical computing libraries.
• Breeze - Breeze is a numerical processing library for Scala.
• Chalk - Chalk is a natural language processing library.
• FACTORIE - FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference.

• Scalding - A Scala API for Cascading
• Summing Bird - Streaming MapReduce with Scalding and Storm
• Algebird - Abstract Algebra for Scala
• xerial - Data management utilities for Scala
• simmer - Reduce your data. A unix filter for algebird-powered aggregation.
• PredictionIO - PredictionIO, a machine learning server for software developers and data engineers.

• Conjecture - Scalable Machine Learning in Scalding
• brushfire - decision trees for scalding
• ganitha - scalding powered machine learning
• adam - A genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.
• bioscala - Bioinformatics for the Scala programming language

• [CoreNLP] (http://nlp.stanford.edu/software/corenlp.shtml) - 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] (http://nlp.stanford.edu/software/lex-parser.shtml) - A natural language parser is a program that works out the grammatical structure of sentences
• [Stanford POS Tagger] (http://nlp.stanford.edu/software/tagger.shtml) - A Part-Of-Speech Tagger (POS Tagger
• [Stanford Name Entity Recognizer] (http://nlp.stanford.edu/software/CRF-NER.shtml) - Stanford NER is a Java implementation of a Named Entity Recognizer.
• [Stanford Word Segmenter] (http://nlp.stanford.edu/software/segmenter.shtml) - 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 Phrasal: A Phrase-Based Translation System
• 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.

• Mahout - Distributed machine learning
• Stanford Classifier - A classifier is a machine learning tool that will take data items and place them into one of k classes.
• Weka - Weka is a collection of machine learning algorithms for data mining tasks

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

• 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 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

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

• NLP - An NLP library for Matlab

• Training a deep autoencoder or a classifier on MNIST digits - Training a deep autoencoder or a classifier on MNIST digits[DEEP LEARNING]
• t-Distributed Stochastic Neighbor Embedding - t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets.
• Spider - The spider is intended to be a complete object orientated environment for machine learning in Matlab.
• LibSVM - A Library for Support Vector Machines
• LibLinear - A Library for Large Linear Classification

• matlab_gbl - MatlabBGL is a Matlab package for working with graphs.
• gamic - Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.

• 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
• Online Learning
• 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
• Dimensionality Reduction - Methods for dimensionality reduction
• NMF - A Julia package for non-negative matrix factorization

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

• 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

• Gladfly - 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

• JuliaCon Presentations - Presentations for JuliaCon
• SignalProcessing - Signal Processing tools for Julia
• Images - An image library for Julia

• Some of the python libraries were cut-and-pasted from vinta
• The few go reference I found where pulled from this page