May 2013

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This is the story of an AK-47 and a dead man named Isaiah.  Because of Isaiah, I forged this AK-47 into a serving ladle.

ak47-into-spoon-arrow

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fryIn this post, we’re going to look at how to manipulate multivariate distributions in Haskell’s HLearn library. There are many ways to represent multivariate distributions, but we’ll use a technique called Markov networks.  These networks have the algebraic structure called a monoid (and group and vector space), and training them is a homomorphism.  Despite the scary names, these mathematical structures make working with our distributions really easy and convenient—they give us online and parallel training algorithms “for free.” If you want to go into the details of how, you can check out my TFP13 submission, but in this post we’ll ignore those mathy details to focus on how to use the library in practice.  We’ll use a running example of creating a distribution over characters in the show Futurama.

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