This the official website of Basics of Statistical Learning (Stat 432). To get started, please read the Course Syllabus.
.pdf
file) to gradescope. Please
use entry code: NYG75N to enroll.Week | Topic |
---|---|
Week 1 (Aug 26) | Introduction |
Week 2 (Sep 2) | Linear Regression and Bias-variance Trade-off |
Week 3 (Sep 9) | Optimization and Ridge Regression (recorded video) |
Week 4 (Sep 16) | Lasso |
Week 5 (Sep 23) | K-nearest neighbors and nonparametric estimation |
Week 6 (Sep 30) | Kernel Methods, Smoothing and Adaptiveness |
Week 7 (Oct 7) | Support Vector Machines |
Week 8 (Oct 14) | Classification and Discriminate Analysis |
Week 9 (Oct 21) | Ensemble Models: Random Forests and Boosting |
Week 10 (Oct 28) | Unsupervised Learning Algorithms |
Week 11 (Nov 4) | RKHS and Related Models |
Week 12 (Nov 11) | Exam, No Class on Nov 14 |
Week 13 (Nov 18) | Casual Inference and Reinforcement Learning |
Week 14 (Nov 25) | Fall Break |
Week 15 (Dec 2) | Final Project Presentation |
Week 16 (Dec 9) | Final Project Presentation |