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 25) Introduction
Week 2 (Sep 1) Linear Regression and Bias-variance Trade-off
Week 3 (Sep 8) Optimization and Ridge Regression
Week 4 (Sep 15) Lasso
Week 5 (Sep 22) K-nearest neighbors and nonparametric estimation
Week 6 (Sep 29) Kernel Methods, Smoothing and Adaptiveness
Week 7 (Oct 6) Support Vector Machines
Week 8 (Oct 13) Classification and Discriminate Analysis
Week 9 (Oct 20) Ensemble Models: Random Forests and Boosting
Week 10 (Oct 27) Unsupervised Learning Algorithms
Week 11 (Nov 3) RKHS and Related Models
Week 12 (Nov 10) Exam
Week 13 (Nov 17) Causal Inference and Personalized Medicine
Week 14 (Nov 24) Fall Break
Week 15 (Dec 1) Final Project Presentation
Week 16 (Dec 8) Final Project Presentation/Q&A

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