CSC 577 - Pattern Recognition Credits: 3
Prerequisite: CSC 340 or equivalent. This course introduces pattern recognition methods and theory using conventional statistical approaches, neural networks, fuzzy logic, support vectors, and linear principal component analysis (PCA). The course also presents methods for non-linear PCA, clustering, and feature extraction. Students implement algorithms; apply methods to selected problems, and to document findings.
Course may only be taken once for credit
Click here for the Fall 2022 Class Schedule.