ITD 240 - Machine Learning II (Fall Spring)

3 cr.

Examines theory, algorithms, applications, and issues within the subfield of pattern recognition and machine learning, including feature engineering and extraction, supervised and unsupervised learning. Focuses on theory and practice, with coverage of underlying mathematical and heuristic concepts. Part II of II.

Lecture Hours: 3
Total Contact Hours: 3

Prerequisite(s): ITD 140