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.
17th–19th June 2009