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by John Melesky
Through the implementation of an honest-to-goodness Bayesian classifier, we'll tour the major topics of supervised machine learning: tokenization, feature selection and vectorization, model training and tuning, and execution. Time permitting, we'll touch on other techniques and topics.
Bring a laptop and an editor -- at the end of the session, you should have your own classifier, understand how it works, and have some ideas for how to make it better.
United States United States, Portland
17th–19th June 2009