STA 142A Statistical Learning I (Winter 2022)
- Instructor: Krishnakumar Balasubramanian
- Lead TA: Tesi Xiao; TA: Wookyeong Song
Please note that you need to have a ucdavis email account to access recorded videos. If you are outside the country, you may probably need a VPN to access it.
| Discussion Topics | Materials | |
|---|---|---|
| Week 1 | Introduction to Python Programming | Link |
| Linear Algebra in Python | Link | |
| Homework and LaTeX | Link | |
| Week 2 | Maximum Likelihood Estimation | Link, Video |
| Week 3 | Bayes Optimal Classifier | Link, Video |
| Python | Link, Video | |
| Week 4 | Classification Methods: Logistic Regression, LDA/QDA, SVM | Link, Video (Part 1), Video (Part 2: SVM) |
| Week 5 | A Review of Loss Functions and Risk | Video |
| Introduction to Numerical Optimization | Link, Video | |
| Week 6 | - | |
| Week 7 | Additive Models, Smoothing Splines, Ensemble Models | Link, Video |
| Week 8 | A Short Tutorial in pyGAM | Link |
| Week 9 | Ridge and LASSO Regression | Video |