Tentative Schedule

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