Spring 2020
COMPSCI 189 001 - LEC 001
Introduction to Machine Learning
Jonathan Shewchuk
Class #:28347
Units: 4
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
11
Enrolled: 728
Waitlisted: 2
Capacity: 739
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 15TH
03:00 pm - 06:00 pm
Internet/Online
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.
Class Notes
* Initial enrollment capacity is set to 70% of total enrollment until TA hiring is complete. We anticipate total enrollment for the COMBINED class to be 744 seats.
* The lecture for this class will be screencast.
* Time conflicts with this class WILL be allowed by the Comp.. show more
* The lecture for this class will be screencast.
* Time conflicts with this class WILL be allowed by the Comp.. show more
* Initial enrollment capacity is set to 70% of total enrollment until TA hiring is complete. We anticipate total enrollment for the COMBINED class to be 744 seats.
* The lecture for this class will be screencast.
* Time conflicts with this class WILL be allowed by the Computer Science department. NOTE: Faculty is NOT obligated to accommodate conflicting final exam times or project due dates.
* This class uses 999 sections. In addition to the lecture, you must in enroll in DIS 999 to enroll in the course. Selection and assignment into the actual discussions happen outside of CalCentral. Instructors will provide more information during the first lecture.
* Grad students MUST enroll into CS 289A. No graduate students will be approved to enroll into CS 189. show less
* The lecture for this class will be screencast.
* Time conflicts with this class WILL be allowed by the Computer Science department. NOTE: Faculty is NOT obligated to accommodate conflicting final exam times or project due dates.
* This class uses 999 sections. In addition to the lecture, you must in enroll in DIS 999 to enroll in the course. Selection and assignment into the actual discussions happen outside of CalCentral. Instructors will provide more information during the first lecture.
* Grad students MUST enroll into CS 289A. No graduate students will be approved to enroll into CS 189. show less
Rules & Requirements
Requisites
- Undergraduate Students - Excludes Visiting Students
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