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University of Texas at Arlington
Computer Science Engineering
Fall 1998


CSE 6363 - Machine Learning
Section 501, TuTh 7:00-8:20pm, 112 Nedderman Hall
URL: http://www-cse.uta.edu/$^\sim$holder/courses/cse6363.html

Description:
A detailed investigation of current machine learning theory and methodologies. Introduces the background and basics of machine learning, including representation, inductive bias and performance evaluation. Analyzes and compares different machine learning methodologies, including statistical, connectionist, symbolic and optimization. Implementations of several methods will be provided for experimentation. Current issues in machine learning research and alternative learning methods will also be examined as they relate to course topics.

Prerequisites:
Artificial Intelligence I (CSE 5360) and II (CSE 5361).

Textbook:
Tom M. Mitchell, Machine Learning, McGraw-Hill, 1997.

Grading:
Five Homeworks (50%), Project (25%), Presentation (15%), Critiques and Class Participation (10%).

Instructor:
Larry Holder, 330 Nedderman Hall, 272-2596, holder@cse.uta.edu.
Office hours: 3-4 Wed, 4-5 Thu.