Added the forked version of the gist by @gbuesing.

Author: arbox

inbox.md

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+Resources for Machine Learning in Ruby
+===
+
+Gems
+---
+
+* [liblinear-ruby](https://github.com/kei500/liblinear-ruby): Ruby interface to LIBLINEAR using SWIG
+
+* [classifier-reborn](https://github.com/jekyll/classifier-reborn): Bayesian and LSI classification
+dependencies: GSL
+
+* [categorize](https://github.com/helioid/categorize): Categorize is a text categorization library written in Ruby. It prioritizes performance over accuracy and is built to run online in dynamic web services
+
+* [decisiontree](https://github.com/igrigorik/decisiontree): ID3-based implementation of the ML Decision Tree algorithm
+dependencies: Graphviz
+
+* [similarity](https://github.com/bbcrd/Similarity):
+Calculate similarity between documents using TF-IDF weights
+dependencies: GSL
+
+* [rb-libsvm](https://github.com/febeling/rb-libsvm):
+Ruby language bindings for LIBSVM
+dependencies: None ([LIBSVM](http://www.csie.ntu.edu.tw/~cjlin/libsvm/) is bundled with the project)
+
+* [ruby-fann](https://github.com/tangledpath/ruby-fann):
+Ruby library for interfacing with FANN (Fast Artificial Neural Network)
+dependencies: None ([FANN](http://leenissen.dk/fann/wp/) is bundled with the project)
+
+* [tlearn-rb](https://github.com/josephwilk/tlearn-rb):
+Recurrent Neural Network library for Ruby
+
+* [kmeans-clusterer](https://github.com/gbuesing/kmeans-clusterer):
+k-means clustering in Ruby
+
+* [k_means](https://github.com/reddavis/K-Means):
+Attempting to build a fast, memory efficient K-Means program
+
+* [knn](https://github.com/reddavis/knn):
+Simple K Nearest Neighbour Algorithm
+
+* [distance_measures](https://github.com/reddavis/Distance-Measures):
+A bunch of distance measures that extend Array
+
+* [fast-stemmer](https://github.com/romanbsd/fast-stemmer):
+Fast Porter stemmer based on a C version of the algorithm
+
+* [statsample](https://github.com/clbustos/statsample):
+A suite for basic and advanced statistics on Ruby
+dependencies: GSL
+
+* [statistics2](https://github.com/abscondment/statistics2):
+Provides normal, Chi-square, t- and F- probability distributions for Ruby
+
+* [ruby-graphviz](https://github.com/glejeune/Ruby-Graphviz)
+dependencies: Graphviz
+
+* [gnuplot](https://github.com/rdp/ruby_gnuplot/tree/master)
+dependencies: Gnuplot
+
+* [rb-gsl](https://github.com/blackwinter/rb-gsl):
+Ruby interface to the GNU Scientific Library
+dependencies: GSL
+
+* [ruby-opencv](https://github.com/ruby-opencv/ruby-opencv/):
+OpenCV wrapper for Ruby
+dependencies: OpenCV
+
+* [ai4r](https://github.com/SergioFierens/ai4r): Artificial Intelligence for Ruby - A Ruby playground for AI researchers
+
+* [algorithms](https://github.com/kanwei/algorithms): Ruby algorithms and data structures. C extensions
+
+* [phashion](https://github.com/westonplatter/phashion): Ruby wrapper around pHash, the perceptual hash library for detecting duplicate multimedia files
+dependencies: ImageMagick, libjpeg
+
+* [narray](https://github.com/masa16/narray): Ruby/NArray : N-dimensional Numerical Array for Ruby
+
+* [kdtree](https://github.com/gurgeous/kdtree) a blazingly fast, native, 2d kdtree
+
+* [rinruby](https://github.com/clbustos/rinruby): integrates the R interpreter in Ruby, making R's statistical routines and graphics available within Ruby
+dependencies: R
+
+* [octave-ruby](https://github.com/daikini/octave-ruby) A Ruby interface to the Octave interpreted language
+dependencies: Octave
+
+* [flann](https://github.com/mariusmuja/flann): Fast Library for Approximate Nearest Neighbors
+dependencies: flann
+
+* [NMatrix](https://github.com/sciruby/nmatrix): Dense and sparse linear algebra library for Ruby via [SciRuby](http://sciruby.com/)
+
+* [Cerebrum](https://github.com/irfansharif/cerebrum): Artificial Neural Networks in Ruby
+
+* [PCA](https://github.com/gbuesing/pca): Principal component analysis (PCA) in Ruby
+
+* [neural-net-ruby](https://github.com/gbuesing/neural-net-ruby): A neural network, written in Ruby
+
+
+
+Base dependencies
+---
+
+* [GSL (GNU Scientific Library)](http://www.gnu.org/software/gsl/)
+```brew install gsl```
+
+* [OpenCV](http://opencv.org/)
+```brew tap homebrew/science && brew install opencv```
+
+* [Graphviz](http://www.graphviz.org/)
+```brew install graphviz```
+
+* [Gnuplot](http://www.gnuplot.info/)
+```brew install gnuplot --with-x11```
+
+* [X11/XQuartz](http://xquartz.macosforge.org/landing/)
+
+* [ImageMagick](http://www.imagemagick.org/) && libjpeg
+```brew install imagemagick && brew install libjpeg```
+
+* [R](http://www.r-project.org/)
+```brew tap homebrew/science && brew install r```
+
+* [Octave](https://www.gnu.org/software/octave/)
+```brew tap homebrew/science && brew install octave --without-docs```
+
+Heroku buildpacks
+---
+
+* [GSL and Ruby buildpack](https://github.com/tomwolfe/heroku-buildpack-gsl-ruby)
+* [OpenCV and Ruby buildpack](https://github.com/lilibethdlc/heroku-buildpack-ruby-opencv)
+* [ImageMagick buildpack](https://github.com/mcollina/heroku-buildpack-imagemagick)
+
+
+Other resources
+---
+
+* [scikit-learn algorithm cheatsheet](http://scikit-learn.org/stable/tutorial/machine_learning_map/)
+* [Thoughtful Machine Learning: A Test-Driven Approach](http://www.amazon.com/Thoughtful-Machine-Learning-Test-Driven-Approach/dp/1449374069)
+* [Support Vector Machines (SVM) in Ruby](https://www.igvita.com/2008/01/07/support-vector-machines-svm-in-ruby/)
+* [Recurrent Neural Networks in Ruby](http://blog.josephwilk.net/ruby/recurrent-neural-networks-in-ruby.html)
+* [Five machine learning techniques that you can use in your Ruby apps today](https://www.youtube.com/watch?v=crziu7dk6Vw) [slides](https://speakerdeck.com/stympy/machine-learning-techniques)