Last week I participated in a webinar on machine learning with Ruby. The specific application revolved on sentiment analysis using support vector machines utilizing the Ruby bindings from the libsvm library.

I'm a big Ruby fan, and wrote glowingly on it for Information Management almost five years ago. Extending the scripting language tradition of Perl and Python, Ruby's ideal for many core munging challenges of data science. The combination of Ruby data types with methods, along with blocks and iterators, can make for very powerful – and terse – code, as this snippet from a portfolio returns program I wrote five years ago illustrates:

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