• Introduction to Artificial Intelligence• Basic Concepts in Machine Learning• Supervised Learning• Unsupervised Learning• Concept Learning• Artificial Neural Networks (ANN)• Genetic Algorithms (GA)• Reinforcement Learning• Bayesian Decision Theory and Bayesin Learning• Statistics for Hypothesis Evaluation• Computational Learning Theory (CLT)• Instance-Based Learning (IBL)• Appendix• Previous Year Examination Papers• Index.
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