big_data_for_chimps by infochimps-labs
A Seriously Fun guide to Big Data Analytics in Practice
created at March 17, 2012, 1:30 a.m.
pynlpl by proycon
PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).
created at July 6, 2010, 11:42 a.m.
skll by EducationalTestingService
SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.
created at Aug. 2, 2013, 2:31 p.m.
Create a dashboard with python!somoclu by peterwittek
Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters
created at Jan. 16, 2013, 6:33 a.m.
SuperLearner by ecpolley
Current version of the SuperLearner R package
created at April 16, 2011, 5:18 a.m.
oz by metasoarous
Data visualizations in Clojure and ClojureScript using Vega and Vega-lite
created at Feb. 12, 2018, 8:10 a.m.
Dora by NathanEpstein
Tools for exploratory data analysis in Python
created at Feb. 16, 2016, 8:27 p.m.
ScikitLearn.jl by cstjean
Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/
created at Feb. 28, 2016, 5:06 p.m.
featureforge by machinalis
A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
created at Feb. 17, 2014, 5:21 p.m.