• 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.

• Author : Dr. Himanshu Sharma
• Publisher : S.K. Kataria & Sons
• Edition : 3rd 2025-26
• Publishing Year : 2022
• Total Pages : 375

About The Author

Himanshu Sharma is a Research Engineer at PNNL. He is currently working to develop and integrate advanced optimization and control methods for energy and power system applications. Earlier, he worked on developing a data-driven Perron-Frobenius operator-based framework for sensor placement for monitoring indoor air quality under uncertainty. His work is geared toward solving challenging problems of complex-physical systems such as energy & smart buildings by leveraging state of the art simulation and data-driven methods.