INTRODUCTION TO MACHINE LEARNING

Catalog description

The course is structured to establish a solid foundation at the intersection of probability and statistics theory with machine learning concepts. Students will cultivate a deep understanding of the core probabilistic principles and tools that serve as the foundation for a wide array of machine learning algorithms and methodologies. The curriculum will extensively delve into both classical and contemporary machine learning theories and algorithms, elucidating their practical application in tasks like classification and regression. PREREQ: (( COMPSCI 332 OR STAT 342 ) AND MATH 355 ) OR INSTRUCTOR CONSENT