Machine Learning frameworks, libraries and software

https://github.com/josephmisiti/awesome-machine-learning

by misiti3780 • 12 years ago

163 35 12 years ago

CSDude• 12 years ago

Weka should be there, it has so many useful tools included and I took a graduate machine learning course and used weka API for its project and it saved me lot of time. Highly recommended.

misiti37808• 12 years ago

added

RussianCow• 12 years ago

I'm surprised at the lack of tools for Java. Do Java developers really not do machine learning? Or is this resource missing some libraries?

misiti37808• 12 years ago

it's definitely missing some libraries. with that said, if you are doing any type of distributed machine learning, you almost have to use java via mahout.

hnriot• 12 years ago

the scala libraries like Factorie work just fine from java.

pickle27• 12 years ago

http://www.shogun-toolbox.org/ has a lot of algorithms, is super fast and has bindings for many languages, check it out!

misiti37808• 12 years ago

added!

kovrik2• 12 years ago

Please, add Clojure and it's libs (see http://www.clojure-toolbox.com).

And sort languages alphabetically, please.

misiti37808• 12 years ago

fixed

kovrik2• 12 years ago

cloJure, not cloSure.

Also, I thought you would add all Machine Learning libs, not just link to the Clojure Toolbox.

orasis• 12 years ago

For Javascript Bayesian Bandits/Thompson Sampling - https://github.com/omphalos/bayesian-bandit.js

misiti37808• 12 years ago

added

tomaskazemekas• 12 years ago

I suggest adding Torch. http://torch.ch/ It is a scientific ML framework written in LuaJIT. Recently it was recommended by Yann LeCun, Director of AI in Facebook. http://www.reddit.com/r/MachineLearning/comments/25lnbt/ama_...

alsocasey• 12 years ago

The R portion needs some serious filling - for starters: you include the Julia wrapper to glmnet, which was originally implemented in R.

glmnet - lasso/ridge/elastic net glm models.

e1071 - SVM classifiers.

randomForest - random forest classifiers.

mixOmics - a good collection of component-based approaches (PCA, ICA, PLS, etc. includes sparse variants of all of the above is feature selection is required).

caret - similar to Java's Weka.

mbq• 12 years ago

Or simply a link to the ML CRAN Task View: http://cran.r-project.org/web/views/MachineLearning.html

silentrob• 12 years ago

Javascript is missing a few NLP tools POS - https://github.com/dariusk/pos-js and Node Natural - https://github.com/NaturalNode/natural

misiti37808• 12 years ago

added

platz2• 12 years ago

How about http://h2o.ai/ ?

misiti37808• 12 years ago

where does it go ?

platz2• 12 years ago

It goes to "The Open Source In-Memory Prediction Engine for Big Data Science"

penetrarthur• 12 years ago

A well maintained library for c# lovers http://accord-framework.net/

jwr3• 12 years ago

A nice list! But this would be significantly more useful if it included project licensing information.

In my case, any library licensed under the GPL is automatically excluded from consideration, so this is a significant factor. I'd rather not spend any time on those.

Radim• 12 years ago

How do you feel about LGPL?

jwr3• 12 years ago

LGPL is a borderline case. On one hand, it doesn't force itself onto all of your software. On the other hand, it contains the same patent claim landmine that the GPL does and that landmine is considered to be dangerous by many lawyers (GPLv2 Section 7, LGPLv2 Section 11).

So, in practical terms, it depends on who my current client/employer/investor is. Myself, I'd rather not use any LGPLd libraries.

S4M• 12 years ago

There is Incanter for Clojure that is missing.

http://incanter.org/

tbueno• 12 years ago

Why do people keep complaining about the content or giving suggestions here? I'm pretty sure the original list was created on Github exactly to encourage contributions (push requests).

micro_cam• 12 years ago

I have a pretty good decision/tree random forest library for go:

https://github.com/ryanbressler/CloudForest

Rickasaurus• 12 years ago

I wish they'd list the license next to each of the projects so I can avoid those that are work unfriendly.

davidy123• 12 years ago

Another huge ecosystem of Java tools is http://gate.ac.uk/

bch• 12 years ago

typo: Julia -> General Purpose ... Kernal Density - Kernel density estimators for julia

elliptic• 12 years ago

In what sense is this list "curated?" I'm seriously asking. Have you used all/most of these, and can recommend them?

captainmuon• 12 years ago

Some more for C++:

- TMVA (Toolkit for Multivariate Analysis): Widely used in physics, esp. particle physics. Has every classifier you can think of and the kitchen sink, neural nets, BDTs, support vector machines, fisher discriminants, etc.. You can use it for parameter estimation, classification, discrimination and other use cases. Is closely integrated with the ROOT framework, which has a few quirks and gives it a bit of a learning curve, but once you get into it it's very easy to make a multivariate analysis. Also has bindings for Python. - http://tmva.sourceforge.net/

- NeuroBayes: Heard some good things about it, but havent tested it. Used in finance and particle physics. Commercial, but they have special licenses for research. I heard integration with TMVA is planned. - http://neurobayes.phi-t.de/index.php/public-information

sroecker• 12 years ago

There is a NeuroBayes plugin for TMVA. I've put it on Github with some additional patches: https://github.com/sroecker/tmva-neurobayes

Machine Learning frameworks, libraries and software

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