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Session

Machine Learning Made Easy with Perl

Lino Ramirez, Sessional Professor, The King's University College

Track: Perl
Date: Wednesday, July 25
Time: 5:20pm - 6:05pm
Location: Portland 256

Machine learning is concerned with the development of algorithms and techniques that allow computers to "learn" from large data sets. This talk presents an overview of a number of machine learning techniques and the main configuration issues the participants need to understand to successfully deploy machine learning applications. The talk also covers three case studies in which we will use Perl scripts to solve real life problems:

  1. Medical decision support systems using support vector machines
  2. Exploratory financial data analysis using fuzzy clustering
  3. Pattern recognition in weather data using neural networks

This talk offers an intensive presentation of machine learning terminology, best practices, standard process, and strategy. Participants will get to know the techniques but more important, they will learn when to use them and why to use them. The talk is appropriate for educators and programmers who want to use machine learning in their own problem domains.