2017 Spring
COMPSCI 289A 001 - LEC 001
Introduction to Machine Learning
Jonathan Shewchuk
Class #:26679
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.
Final Exam
MON, MAY 8TH
03:00 pm - 06:00 pm
RSF Fieldhouse
Other classes by Jonathan Shewchuk
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
Textbooks & Materials
Textbook information is not available for Spring 2017.