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CS 584: Machine Learning

Objectives

Prerequisites

Syllabus

Introduction 1.5 hours
Version space learning; Computational learning theory 4.0 hours
PAC-learning; VC-dimension; On-line learning; Winnow 4.0 hours
Perceptrons; Neural Networks; Backpropagation 6.0 hours
Genetic algorithms 3.5 hours
Bayesian learning 3.5 hours
Experimental design 3.0 hours
Decision-tree learning 3.5 hours
Covering algorithms for learning rule sets 3.0 hours
Minimum description length 3.5 hours
Clustering algorithms 3.0 hours
Reinforcement learning 3.5 hours
Markov decision processes 3.0 hours
Total 45 hours

Edited March 2006 (html, css checks)