Artificial Intelligence-Theory and Practice

Artificial Intelligence-Theory and Practice offers a comprehensive journey through the key areas of artificial intelligence, providing readers with both foundational knowledge and insights into advanced topics. The book begins with an overview of AI as a discipline, exploring its definition, historical development, types of intelligence, and major milestones. It introduces core mathematical concepts essential to understanding AI systems, such as linear algebra, probability, statistics, calculus, and optimization techniques. These tools form the analytical basis for many AI methods and models. The book proceeds to discuss classical AI approaches to problem solving, including state-space search techniques and both uninformed and informed algorithms. It examines adversarial search strategies used in competitive environments and dives into knowledge representation and reasoning-focusing on logic-based systems, ontologies, and probabilistic reasoning methods that enable machines to draw conclusions and make decisions.

A significant portion of the book is devoted to machine learning. Readersare introduced to key learning paradigms-supervised, unsupervised, and reinforcement learning-and the process of model selection and evaluation. It explains classical machine learning algorithms such as regression, decision trees, support vector machines, and clustering techniques. The book then explores deep learning, covering artificial neural networks, convolutional and recurrent architectures, autoencoders, generative adversarial networks (GANs), and transfer learning, all of which have enabled breakthroughs in modern AI applications. Specialized fields such as natural language processing and computer vision are explored in depth. Topics include tokenization, syntactic analysis, word embeddings, and powerful transformer models like BERT and GPT. The computer vision section discusses image analysis techniques, convolutional neural networks, and newer architectures like vision transformers.

AUTHOR BIOGRAPHIES

Dr. Amit Kumar Mehar

Author

Dr. Amit Kumar Mehar is an Associate Professor in the Department of Mechanical Engineering, Raghu Engineering College (REC), Vishakhapatnam, Andhra Pradesh, India. He has 3 years of industrial, 15 years of teaching, and 6 years of research experience in his field. He has published more than 20 papers in various international journals in repute, 4 national and 8 international conferences, and 5 book chapters. He has 10 professional memberships. He has published more than 10 patents in his field. He did B.E. in Mechanical Engineering from Guru Ghasidas University (Now A Central University), Bilaspur (C.G.), India in 2006. He did M. Tech. with Manufacturing Specialization in Mechanical Engineering from N.I.T., Rourkela (Odisha), India in 2011. He did Ph.D. in Mechanical Engineering in Manufacturing area from N.I.T., Rourkela (Odisha), India in 2017. He is expertise in Composite Materials, Biomaterials, Bio-Composites, Tribology, Machining, Optimization Techniques, Artificial Intelligence, Machine Learning, and Internet of Things.

Dr. Raj Kumar Sahu

Author

Dr. Raj Kumar Sahu is an experienced academician and researcher in Electrical and Electronics Engineering, born in 1981 in Bhilai, Durg, India. He holds a B.E. in Electronics and Communication Engineering from MANIT Bhopal (2004), an M.Tech in Digital Electronics (2009), and a Ph.D. in Electrical Engineering from NIT Raipur (2022). With over 18 years of teaching experience, he has served as Associate Professor at CSIT Durg and as Temporary Faculty in Biomedical Engineering at NIT Raipur. He currently works as an Assistant Professor in the Department of Electronics and Communication Engineering at Amity University, Raipur, Chhattisgarh. Dr. Sahu’s areas of expertise include artificial intelligence, forecasting, control systems, optimization, and renewable energy systems, particularly Solar PV. He is known for promoting innovative project work, real-world problem-solving, and a teaching approach centered on self-study and case-based learning.

Mr. S M K Sukumar Reddy

Author

Mr. S M K Sukumar Reddy is an Associate Professor and Head of Department in Electronics & Communication Engineering at Vaagdevi Institute of Technology and Science, Proddatur. With over 17 years of teaching experience, he is pursuing Ph.D in Electronics and Communication Engineering in the area of Wireless Sensor Networks, completed M.Tech at MSRIT Bangalore and B.Tech at JNTUH Hyderabad. Recognized with numerous awards for his excellence in teaching, his expertise spans Signal Processing, Error Control Coding, Optical Communications, and Wireless Sensor Networks. His contributions include authoring textbooks, publishing research in national and international journals, attending national conferences, securing one Canadian copyright, and obtaining three Indian design patents. Additionally, he has served as a reviewer for an international conference.

Dr. U. D. Prasan

Author

Dr. U. D. Prasan has been serving as a Professor in the Department of Computer Science and Engineering at AITAM, Tekkali since 2007. With a rich teaching experience spanning over 24 years, he has contributed significantly to the academic and research domains. He was awarded a Ph.D. in Computer Science and Engineering in May 2016, with a specialization in Sensor Networks. He has published numerous research papers in reputed international journals with high impact factors and has presented his work at various national and international conferences. He holds patents and has served as a reviewer for several international journals and conferences, reflecting his active engagement in the global research community. His research interests include Computer Networks, Data Mining, Image Processing, Operating Systems, and Machine Learning.