| description |
Through the implementation of an honest-to-goodness Bayesian classifier, weâll tour the major topics of supervised machine learning: tokenization, feature selection and vectorization, model training and tuning, and execution. Time permitting, weâll touch on other techniques and topics.
About the speaker:
John Meleskyâs been programming on the web since gopher was a legitimate competitor. He is an independent consultant who specializes in machine learning, natural language processing, and how those are applied to the web. |
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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.
About the speaker:
John Melesky’s been programming on the web since gopher was a legitimate competitor. He is the team lead for the Analytics team at Janrain, where he gets to get his hands covered in all sorts of interesting data. |