Course ID
035539
Course Description
Machine learning describes the development of algorithms which can modify their internal parameters (i.e., \"learn\") to recognize patterns and make decisions based on example data. These examples can be provided by a human, or they can be gathered automatically as part of the learning algorithm itself. This course will introduce the fundamentals of machine learning, will describe how to implement several practical methods for pattern recognition, feature selection, clustering, and decision making for reward maximization, and will provide a foundation for the development of new machine learning algorithms.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Graduate
Course Attributes
GIDP - COGS (Cognitive Science), GIDP - GC (Global Change), GIDP - NRSC (Neuroscience), GIDP - SLAT (Sec. Lang. Acquisition & Teach), GIDP - STATD (Statistics and Data Science)
May be convened with
ISTA421
Component
Lecture
Optional Component
No