CPSC - 6575 Machine Learning Fundamentals 3

Introduces key mathematical and computational topics along with the processes, patterns, and strategies needed to build effective computer systems that learn from experience. Presents approaches to training and evaluating such learning systems. Acquaints students with feature engineering approaches to transforming ambiguous data into useful forms for machine learning. Instructional Method: LD Lecture-Discussion. Semester Offered: Spring. Prerequisite: the undergraduate course equivalents to Applied Calculus and Introduction to Object-oriented Programming.