MSSC 6250 - Statistical Machine Learning (Spring 2025)

This schedule will be updated as the semester progresses, with all changes documented here.

Week Date Topic To Do Slides Code Homework Project
1 Tue, Jan 14 Syllabus/Overview of Statistical Learning 📖 🖥️🖥️
Thu, Jan 16 Bias-variance tradeoff 🖥️
2 Tue, Jan 21 NO CLASS: Cold Weather 📖 🖥️
Thu, Jan 23 Linear Regression
3 Tue, Jan 28 Numerical Optimization 📖 ✍️ HW1
Thu, Jan 30 Stochastic Gradient Descen; Ridge Regression 🖥️
4 Tue, Feb 4 Cross-Validation; Feature Selection 📖 🖥️
Thu, Feb 6 LASSO
5 Tue, Feb 11 Regression Splines 📖 🖥️
Thu, Feb 13 Smoothing Splines and Generalized Additive Models HW 1 Due
6 Tue, Feb 18 Bayesian Inference and Linear Regression 📖 🖥️ ✍️ HW2
Thu, Feb 20 Bayesian Linear Regression ✅ Team up Due
7 Tue, Feb 25 Binary Logistic Regression 📖 🖥️
Thu, Feb 27 Multinomial Logistic Regression HW 2 Due ✅ Proposal Due
8 Tue, Mar 4 Discriminant Analysis 📖 🖥️
Thu, Mar 6 Midterm Presentation I ✍️ HW3 ✅ Materials Due
9 Tue, Mar 11 NO CLASS: Spring break
Thu, Mar 13 NO CLASS: Spring break Deep Learning Workshop (Fri, Mar 14)
10 Tue, Mar 18 Naive Bayes 📖
Thu, Mar 20 K-Nearest Neighbors 🖥️
11 Tue, Mar 25 Gaussian Process Regression 📖 🖥️
Thu, Mar 27 Gaussian Process Classification
12 Tue, Apr 1 Support Vector Machine 📖 🖥️
Thu, Apr 3 Support Vector Machine HW 3 Due
13 Tue, Apr 8 CART and Bagging 📖 🖥️
Thu, Apr 10 Random Forests and Boosting ✍️ HW4
14 Tue, Apr 15 Midterm Presentation II 📖 🖥️ ✅
Thu, Apr 17 NO CLASS: Easter break
15 Tue, Apr 22 Principal Component Analysis 📖 🖥️
Thu, Apr 24 K-Means Clustering
16 Tue, Apr 29 Model-based Clustering 📖 🖥️
Thu, May 1 Neural Networks
17 Thu, May 8 Final Project Submission ✅

I reserve the right to make changes to the schedule.