Spring 2019
COMPSCI 289A 106 - DIS 106
Introduction to Machine Learning
Vasilis Oikonomou
Class #:28507
Units: 4
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
0
Enrolled:
Waitlisted:
Capacity:
Waitlist Max:
No Reserved Seats
Hours & Workload
8 hours of outside work hours per week, 1 hours of the exchange of opinions or questions on course material per week, and 3 hours of instructor presentation of course materials per week.
Other classes by Vasilis Oikonomou
Course Catalog Description
This course provides an introduction to theoretical foundations, algorithms, and methodologies for machine learning, emphasizing the role of probability and optimization and exploring a variety of real-world applications. Students are expected to have a solid foundation in calculus and linear algebra as well as exposure to the basic tools of logic and probability, and should be familiar with at least one modern, high-level programming language.
Rules & Requirements
Credit Restrictions
Students will receive no credit for Comp Sci 289A after taking Comp Sci 189.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats