Instructor: Dogyoon Song (dgsong [at] ucdavis [dot] edu)
Teaching Assistant: Yanhao Jin (yahjin [at] ucdavis [dot] edu)
Lectures: Mondays, Wednesdays and Fridays, 1:10 PM – 2:00 PM, Wellman Hall 6
Discussions (Labs) are run by TA
Office hours:
Syllabus: link
Canvas: link
Piazza: link
Textbooks: There is one required textbook, which is available online.
A tentative list of topics to be covered include:
The students’ performance in this course will be evaluated based on the following:
| Lecture Day | Topics | Slides | Additional references | HW | Notes |
|---|---|---|---|---|---|
| Mon, Mar 30 | Introduction | Lecture 1 | JWHT, Ch 1 | “HW 0” | |
| Wed, Apr 1 | Probability review: basics and conditional probability | Lecture 2 | Homework 1 posted; due Tue, April 7 | ||
| Fri, Apr 3 | Probability review: Bayes’ theorem and random variables | Lecture 3 | |||
| Mon, Apr 6 | Statistical learning | Lecture 4 | JWHT, Ch 2.1 | ||
| Wed, Apr 8 | Simple linear regression | Lecture 5 | JWHT, Ch 3.1 | Homework 2 posted; due Tue, April 14 | |
| Fri, Apr 10 | Multiple linear regression | Lecture 6 | JWHT, Ch 3.2 & 7.1 | ||
| Mon, Apr 13 | Qualitative predictors & pitfalls in linear regression | Lecture 7 | JWHT, Ch 3.3 & 3.5 | ||
| Wed, Apr 15 | Classification & Logistic regression | Lecture 8 | JWHT, Ch 4.1-4.3 | Homework 3 posted; due Tue, April 21 | |
| Fri, Apr 17 | Logistic regression (cont’d) & Classification errors | Lecture 9 | JWHT, Ch 4.3-4.4 | ||
| Mon, Apr 20 | Generative models & Linear discriminant analysis | Lecture 10 | JWHT, Ch 4.4 | ||
| Wed, Apr 22 | More on generative models + Review for Midterm 1 | Lecture 11 | JWHT, Ch 4.4-4.5 | ||
| Fri, Apr 24 | Midterm1 (in-class) | Solution | |||
| Mon, Apr 27 | The bias-variance tradeoff | Lecture 12 | JWHT, Ch 2.2 | ||
| Wed, Apr 29 | Cross-validation | Lecture 13 | JWHT, Ch 5.1 | Homework 4 posted; due Tue, May 5 | |
| Fri, May 1 | k-fold CV & The bootstrap | Lecture 14 | JWHT, Ch 5.2 | ||
| Mon, May 4 | Subset selection | Lecture 15 | JWHT, Ch 6.1 | Remote lecture; see Canvas announcement | |
| Wed, May 6 | Regularization | Lecture 16 | JWHT, Ch 6.2 | Homework 5 posted; due Tue, May 12 | |
| Fri, May 8 | Regularization (cont’d) & Multiple testing | Lecture 17 | JWHT, Ch 6.2 & 13.1-13.2 | ||
| Mon, May 11 | Multiple hypotheses testing | Lecture 18 | JWHT, Ch 13.2-13.4 | ||
| Wed, May 13 | Review for Midterm 2 | Lecture 19 | |||
| Fri, May 15 | Midterm2 (in-class) | Solution | |||
| Mon, May 18 | Basis functions & Regression splines | Lecture 20 | JWHT, Ch 7.1-7.4 | ||
| Wed, May 20 | Natural splines + Smoothing splines | Lecture 21 | JWHT, Ch 7.4-7.5 | Homework 6 posted; due Tue, May 26 | |
| Fri, May 22 | Principal component analysis | Lecture 22 | JWHT, Ch 6.3.1 & 12.1-12.2 | ||
| Mon, May 25 | Memorial day, no class | ||||
| Wed, May 27 | Principal component analysis (cont’d) | Lecture 23 | JWHT, Ch 12.2 | Homework 7 posted; due Tue, June 2 | |
| Fri, May 29 | Clustering: K-means clustering | Lecture 24 | JWHT, Ch 12.4 | ||
| Mon, Jun 1 | Clustering: Hierarchical clustering | Lecture 25 | JWHT, Ch 12.4 | ||
| Wed, Jun 3 | Review for final exam & Conclusion | Lecture 26 | |||
| Fri, Jun 5 | Final exam (1:00 - 3:00 PM) | Solution |
Sample exams from the previous year (Spring 2025):
Additional mock exams for practice: