UNIT - I Introduction - Well-posed learning problems, designing a learning system, Perspectives and issues in machine learning. Concept learning and the general to specific ordering - introduction, a concept learning task, concept learning as search, find-S : finding a maximally specific hypothesis, version spaces and the candidate elimination algorithm, remarks on version spaces and candidate elimination, inductive bias. Decision Tree Learning - Introduction, decision tree representation, appropriate problems for decision tree learning, the basic decision tree learning algorithm, hypothesis space search in decision tree learning, inductive bias in decision tree learning, issues in decision tree learning. (Chapter - 1) UNIT - II Artificial Neural Networks UNIT - III Bayesian learning UNIT-IV Genetic Algorithms UNIT-V Analytical Learning
