Spring 2019
COMPSCI 189 001 - LEC 001
Introduction to Machine Learning
Jonathan Shewchuk
Class #:28076
Units: 4
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
-1
Enrolled: 682
Waitlisted: 1
Capacity: 681
Waitlist Max: 0
No Reserved Seats
Hours & Workload
1 hours of the exchange of opinions or questions on course material per week, 3 hours of instructor presentation of course materials per week, and 8 hours of outside work hours per week.
Final Exam
FRI, MAY 17TH
03:00 pm - 06:00 pm
Wheeler 150
Other classes by Jonathan Shewchuk
Course Catalog Description
Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression and classication (linear models, trees, neural networks, ensemble methods, instance-based methods); generative and discriminative probabilistic models; Bayesian parametric learning; density estimation and clustering; Bayesian networks; time series models; dimensionality reduction; programming projects covering a variety of real-world applications.
Rules & Requirements
Credit Restrictions
Students will receive no credit for Comp Sci 189 after taking Comp Sci 289A.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats