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CM 764Statistical Learning - Advanced Regression

Units
0.50
Level
Graduate
Faculty
Mathematics
Subject
Computational Mathematics
Cross-listed
STAT 844

When it runs

  1. F24
  2. W25
  3. S25
  4. F25
  5. W26
  6. S26
  7. F26
  8. W27
  9. S27

Ran in 4 of the last 7 terms. Winter 2027: scheduled, 1 lecture section. Spring 2027: schedule not out yet.

This course introduces modern applied regression methods for continuous response modelling, emphasizing both explainability and predictive power. Topics cover a wide selection of advanced methods useful to address the challenges arising from real-world and high-dimensional data; methods include robust regression, nonparametric regression such as smoothing splines, kernels, additive models, tree based methods, boosting and bagging, and penalized linear regression methods such as the ridge regression, lasso, and their variants. Students will gain an appreciation of the mathematical and statistical concepts underlying the methods and also computational experience in applying the methods to real data.

Prerequisites

None listed.

Antirequisites

  • Not completed nor concurrently enrolled in:

Leads to

No course lists it as a requisite.

Winter 2027 sections

Enrolment from UW Open Data, which can trail Quest by up to two days. Instructors and rooms: Schedule of Classes.
SectionClassEnrolledMeets
LEC 00157970 / 10TTh 13:00–14:20

Check it elsewhere for Fall 2026

Calendar versions

Graduate Calendar

Older Graduate Calendars

In 33 terms, Fall 2009 to Winter 2024