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Unit - 1 Introduction

1.1 INTRODUCTION – Well defined learning problems 1.2 Design of a learning system

1.3 Issues in Machine Learning

1.4 Concept Learning

1.5 Generaltospecific ordering of hypotheses

1.6 FindS Finding a Maximally Specific Hypothesis

1.7 ListthenEliminate Algorithm

1.8 CE CandidateElimination Algorithm

1.1 INTRODUCTION – Well defined learning problems

1.2 Design of a learning system

1.3 Issues in Machine Learning

1.4 Concept Learning

1.5 Generaltospecific ordering of hypotheses

1.6 FindS Finding a Maximally Specific Hypothesis

1.7 ListthenEliminate Algorithm

1.8 CE CandidateElimination Algorithm

Unit - 2 Decision tree learning

2.1 Decision tree learning algorithm 2.2 ARTIFICIAL NEURAL NETWORKS

2.1 Decision tree learning algorithm

2.1 Decision tree learning algorithm

2.2 ARTIFICIAL NEURAL NETWORKS

2.1 Decision tree learning algorithm

2.2 ARTIFICIAL NEURAL NETWORKS

Unit - 3 Evaluating Hypotheses

3.1 Evaluating Hypotheses Estimating Hypotheses Accuracy3.2 Bayesian Learning Bayes theorem Concept learning Bayes Optimal Classifier

3.1 Evaluating Hypotheses Estimating Hypotheses Accuracy

3.2 Bayesian Learning Bayes theorem Concept learning Bayes Optimal Classifier

3.1 Evaluating Hypotheses Estimating Hypotheses Accuracy

3.2 Bayesian Learning Bayes theorem Concept learning Bayes Optimal Classifier

3.1 Evaluating Hypotheses Estimating Hypotheses Accuracy

3.2 Bayesian Learning Bayes theorem Concept learning Bayes Optimal Classifier

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