How to: Scientific
* Bindings
  * [PyCall](https://github.com/mrkn/pycall.rb) - Calling Python functions from the Ruby language.
  * [ruby-opencv](https://github.com/ruby-opencv/ruby-opencv) - An OpenCV wrapper for Ruby.
* Classifiers
  * [classifier-reborn](https://github.com/jekyll/classifier-reborn) - An active fork of Classifier, and general module to allow Bayesian and other types of classifications.
* Data analysis/structures
  * [daru](https://github.com/v0dro/daru) - A library for storage, analysis, manipulation and visualization of data in pure Ruby.
  * [Daru::View](https://github.com/SciRuby/daru-view) - A library for easy and interactive plotting on Jupyter Notebooks and web applications.
  * [Rgl](https://github.com/monora/rgl) - A framework for graph data structures and algorithms.
* Numerical arrays
  * [NMatrix](https://github.com/sciruby/nmatrix) - Fast numerical linear algebra library for Ruby.
  * [Numo::NArray](https://github.com/ruby-numo/numo-narray) - N-dimensional Numerical Array for Ruby.
  * [mdarray](https://github.com/rbotafogo/mdarray) - Multi dimensional array implemented for JRuby inspired by NumPy.
* [Red Data Tools](https://github.com/red-data-tools) - Data processing tools for Ruby.
* [SciRuby](https://github.com/sciruby/sciruby) - Tools for scientific computation in Ruby/Rails.
  * [IRuby](https://github.com/SciRuby/iruby) - A Ruby kernel for Jupyter.
  * [statsample](https://github.com/sciruby/statsample) - A suite for basic and advanced statistics on Ruby.
  * [statsample-timeseries](https://github.com/sciruby/statsample-timeseries) - Bioruby Statsample TimeSeries.
  * [statsample-glm](https://github.com/sciruby/statsample-glm) - Generalized Linear Models extension for Statsample.
  * [distribution](https://github.com/sciruby/distribution) - Statistical Distributions multi library wrapper.
  * [minimization](https://github.com/sciruby/minimization) - Minimization algorithms on pure Ruby.
* Specific
  * [BioRuby](https://github.com/bioruby/bioruby) - Library for developing bioinformatics software.
  * [bloomfilter-rb](https://github.com/igrigorik/bloomfilter-rb) - BloomFilter(s) in Ruby: Native counting filter + Redis counting/non-counting filters.
  * [decisiontree](https://github.com/igrigorik/decisiontree) - A ruby library which implements ID3 (information gain) algorithm for decision tree learning.
* Utilities
  * [algorithms](https://github.com/kanwei/algorithms) - Library with documentation on when to use a particular structure/algorithm.
  * [jaro_winkler](https://github.com/tonytonyjan/jaro_winkler) - Ruby & C implementation of Jaro-Winkler distance algorithm which supports UTF-8 string.
  * [primes-utils](https://github.com/jzakiya/primes-utils) - A Rubygem which provides a suite of extremely fast utility methods for testing and generating primes.
  * [Roots](https://github.com/jzakiya/roots) - A Rubygem which provides utilities to find all the nth roots of real and complex values.
  * [smarter_csv](https://github.com/tilo/smarter_csv) - Ruby Gem for smarter importing of CSV Files as Array(s) of Hashes.