Lecture Slides	Aid Materials	Assignments
0. Outline 1. The Elements of Statistical Learning 2. Linear Algebra Review 3. Probability Review	TAKE-HOME EXAM
1. Introduction	· Ethem’s Slides (modified)
2. Concept Learning	· Ethem’s Slides (modified)
3. Decision Tree Learning	Tutorial on Decision Trees Tutorial on Information Gain Ethem’s Slides (modified) ASSIGNMENT #2
4. Artificial Neural Networks	60-561: Chap 1 60-561: Chap 2 60-561: Chap 3 Ethem’s Slides Tutorial on Neural Networks Support Vector Machines
5. Evaluating Hypotheses	Tutorial on Cross Validation
6. Bayesian Learning	Tutorial on Bayesian Networks I Tutorial on Inference in Bayesian Networks II Tutorial on Learning Bayesian Networks III Tutorial on Naive Bayes Classifier Hidden Markov Models Probability for Data Miners
7. Computational Learning Theory	Computational (pdf) Computational (ppt)
8. Instance Based Learning	Tutorial on Instance Based Learning
9. Genetic Algorithms	Tutorial on Hillclimbing, Simulated Annealing and Genetic Algorithms
10. Learning Sets of Rules	Not Available
11. Analytical Learning	Not Available
12. Combining Inductive and Analytical Learning	Not Available
13. Reinforcement Learning	Tutorial on Reinforcement Learning