Remember: there is no excuse for ignorance of the assigned reading material. Visit this page frequently. Bring a friend. Start a party.

Date	Topic	Reading	Out	In
Jan 11	Introduction and Overview	Chapter 1	7641 Group Project
Jan 13	Supervised Learning Review: Neural Networks & Decision Trees	Chapters 3 & 4
Jan 18	Instance Based Learning	Chapter 8	Assignment 1
Jan 20	Support Vector Machines	handouts		Team Formation
Jan 25	Support Vector Machines Boosting	handouts
Jan 27	Bayesian Learning	Chapter 6		Informal Proposal
Feb 1	Bayesian Learning
Feb 3	Bayesian Learning
Feb 8	Computational Learning Theory	Chapter 7
Feb 10	Computational Learning Theory			Formal Proposal Keywords Assignment 1 (2/11)
Feb 15	Addressing Overfitting Information Theory	Chapter 5 handouts
Feb 17	Randomized Optimization	Chapter 9	Assignment 2
Feb 22	Randomized Optimization	handouts
Feb 24	Overflow			Suggestions re: Formal Proposals (2/27)
March 1	Midterm Exam
March 3 Drop Day is 3/4	Exam Review
March 8	Clustering	handouts
March 10	Clustering Expectation Maximization	Chapter 6 (again) handouts	Assignment 3	Assignment 2 (3/11)
March 15	Feature Selection	handouts
March 17	Feature Transformation
March 22 March 24	Spring Break
March 29	Feature Transformation
March 31	Markov Decision Processes			Progress Report
April 5	Reinforcement Learning	Chapter 13	Assignment 4
April 7	Reinforcement Learning			Submitted Papers, Assignment 3 (4/9)
April 12	Reinforcement Learning
April 14	Game Theory	handouts		Review of Final Papers
April 19	Game Theory	handouts
April 21	Overflow			Final Project Material (4/22)
April 26 April 28	Final Presentations			Review of Final Presentations (4/28) Assignment 4
May 2	Final Exam 11:30-2:20