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

Python

Natural Language Processing

• 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 Segementation Utilities.
• SnowNLP - A library for processing Chinese text.
• loso - Another Chinese segmentation library.
• genius - A Chinese segment base on Conditional Random Field.

General-Purpose Machine Learning

• 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.

Data Analysis / Data Visualization

• 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.

Ruby

Natural Language Processing

• Treat - Text REtrieval and Annotation Toolkit, definitely the most comprehensive toolkit I’ve encountered so far for Ruby
• Ruby Linguistics - NLTK for Ruby
• Stemmer
• Ruby Wordnet
• Raspel
• UEA Stemmer

General-Purpose Machine Learning

• Ruby Machine Learning
• Machine Learning Ruby
• jRuby Mahout
• CardMagic-Classifier

Data Analysis / Data Visualization

rsruby data-visualization-ruby ruby-plot plot-rb scruffy

Scala

Java

Go

R

Julia

Credits

• Some of the python libraries were cut-and-pasted from vinta