CSCI 447 - Machine Learning

3 credits (3 hrs Lec)

Introduction to the framework of learning from examples. Topics include various learning algorithms such as neural networks, Bayesian networks, and genetic algorithms, and generic learning principles such as bias/variance, MDL principle, and ethical considerations. Review statistical learning techniques, yet focuses on non-statistical techniques. Students may not take this course for both 400 and 500 level credit.

Prerequisite(s): CSCI 332 and STAT 216 or higher