Date | Topic | Reading |
---|---|---|
May 12 | Introduction and Overview | Alpaydin Ch 1, 2 Mitchell Ch 1 |
May 14 | Decision Trees | Alpaydin Ch 9 Mitchell Ch 3 |
May 19 | Neural Networks | Alpaydin Ch 11 Mitchell Ch 4 |
May 21 | Support Vector Machines, Instance-based Learning | Alpaydin Ch 13 Mitchell Ch 8 |
May 22 | Team Formation and Project Abstract due | |
May 26 | Ensemble Learning, Model Selection | Alpaydin Ch 17, 19 |
May 28 | Bayesian Learning | Alpaydin Ch 3, 14 Mitchell Ch 6 |
June 2 | Bayesian Inference | Alpaydin Ch 3, 14 Mitchell Ch 6 |
June 3 | Assignment 1 due | |
June 4 | Computational Learning Theory | Mitchell Ch 7 |
June 9 | Dimensionality Reduction | Alpaydin Ch 6 |
June 10 | Informal Project Proposal due | |
June 11 | Dimensionality Reduction | Alpaydin Ch 6 |
June 16 | Clustering, Midterm Review | Alpaydin Ch 7 |
June 18 | Midterm Exam | |
June 23 | Clustering | Alpaydin Ch 7 |
June 25 | Midterm Exam Review | |
June 30 | Optimization | Mitchell Ch 9 |
July 1 | Assignment 2 due | |
July 2 | Markov Models | Alpaydin Ch 15 |
July 7 | Markov Decision Processes | Alpaydin Ch 18 |
July 8 | Project Progress Report due | |
July 9 | Reinforcement Learning | Alpaydin Ch 18 Mitchell Ch 13 |
July 14 | Game Theory | |
July 16 | Real-world Machine Learning | |
July 17 | Final Project Report due | |
July 21 | Project Presentations | |
July 23 | Course Review | |
July 27 | Finals Week |