Date Topic Read Ch. Assignment/Exam 14 Jan Introduction,Concept Learning and Inductive Bias 1 & 2 21 Jan Evaluating Hypotheses, k-NN and Naive Bayes 5,6.1-6.2,6.9-6.10 & 8.1-8.2 PA1 out 28 Jan Theoretical Frameworks 6.3-6.8 & 7 4 Feb Decision Tree Classifiers 3 PA2 out 11 Feb Pragmatic Considerations of Learning notes+paper1+paper2 25 Feb Neural Network Learning 4 4 Mar Combining Classifiers Pages 1-14 of Dietterich's paper PA3 out Schapire's boosting paper Pages 1-16 of Burges' paper 11 Mar Learning with Kernels 18 Mar Reinforcement Learning I 13 project out 25 Mar Reinforcement Learning II papers 1 Apr Learning with Incomplete Data papers 8 Apr Project Presentations, Reflections and Review for final exam