Machine Learning (CSE 6363) Fall 1997
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
Prerequisites: Artificial Intelligence I (CSE 5360) and
Artificial Intelligence II (CSE 5361).
Textbook: Tom M. Mitchell, Machine Learning,
Grading: Five Homeworks (50%), Project (25%), Presentation
(15%), Critiques and Class Participation (10/%).
Larry Holder , 330 Nedderman Hall, 272-2596, firstname.lastname@example.org.
Office hours: 5-6:30pm TuTh.
ML2.0 System is a framework for
comparing several different learning algorithms. Written in C.
Lawrence B. Holder
Department of Computer Science and Engineering
University of Texas at Arlington
Box 19015, Arlington, TX 76019-0015
phone: (817) 272-2596, fax: (817) 272-3784