Welcome!

This the official website of Basics of Statistical Learning (Stat 432). To get started, please read the Course Syllabus.


Lectures and Homework


Office Hour


Tentative Schedule

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

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