Track: Bioinformatics 2003 Tutorial
Date: Monday, February 03
Time: 1:30pm - 5:00pm
Williams provides an introduction to some classic Machine Learning (ML) techniques using Perl. Perl is not traditionally associated with ML, but its broad reach and expressive characteristics provide an attractive alternative to the more common ML languages like C and Lisp.
The tutorial draws from several sources, especially Tom Mitchell's book, Machine Learning, as inspiration for techniques presented. Special emphasis will be placed on the subject of Text Categorization, an area of active research and wide applicability.
Williams presumes no significant experience in ML of his audience, but a good working knowledge of Perl is helpful. Williams notes, "Perl isn't traditionally used much for Machine Learning, but it's used quite a bit for 'practical' data problems. My talk focuses on how Perl can be used for Machine Learning in a practical way. After my session, attendees should be able to use the Perl modules and techniques I discuss in my presentation to solve their problems."
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