If you are a Rubyist/Ruby developer willing to start playing with machine learning in your favorite language this post is for you. Apache Mahout is an open source machine learning library written in Java that allows engineers to work with ridiculous amounts of data to build recommendation engines, classifiers and cluster analysis tools. Once scaled with a Hadoop cluster, it becomes even more superior, being able to deal with billions of data points in a blink.

I always wondered why there is no good machine learning library for Ruby. So after much research and googling, i found a gem /library named JRuby Manhout. Why JRuby? The answer is simple: it uses JVM and allows for easy integration with Java libraries. Basically, by switching to JRuby, you can use all of your regular Ruby goodness plus implement interfaces from Java libraries. Apache Mahout is a library for machine learning that effectively deals with recommendations, clustering, classification, pattern mining, regression and other related things. Mahout is the core of the JRuby Mahout gem.

Installing Mahout for basic purposes is easy: simply download Mahout 0.7 from one of the official mirrors, unzip the file and setup the environmental variable MAHOUT_DIR that points at your Mahout installation. Mahout is a Java library, so you’ll have to install JVM and JRuby on your machine. For JRuby installation instructions check out the official website. After you got JRuby and Mahout installed, it’s time to setup the project. Create a Gemfile in your project directory and hook up jruby_mahout. Happy coding