Artificial Intelligence By Janakiraman Ebook
CRC Press English 2018 ISBN-10: 480 Pages PDF 8.13 MB by Richard E. Neapolitan (Author), Xia Jiang (Author) The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI.
The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding.
Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more. About the Author Richard E. Neapolitan is professor emeritus of computer science at Northeastern Illinois University and a former professor of bioinformatics at Northwestern University. He is currently president of Bayesian Network Solutions.
Artificial intelligence is a hard subject to learn. The author have written a book to make it easier. He explains difficult concepts in a simple, concrete way. This book is intended for all first courses in artificial intelligence. (17757 views) Foundations of Constraint Satisfaction by Edward Tsang - Academic Press, 1993. Artificial Intelligence for.NET Book Description: Get introduced to the world of artificial intelligence with this accessible and practical guide. Build applications that make intelligent use of language and user interaction to better compete in today’s marketplace.
His research interests include probability and statistics, decision support systems, cognitive science, and applications of probabilistic modeling to fields such as medicine, biology, and finance. What is 64-bit. Neapolitan is a prolific author and has published in the most prestigious journals in the broad area of reasoning under uncertainty. He has previously written five books, including the seminal 1989 Bayesian network text Probabilistic Reasoning in Expert Systems; Learning Bayesian Networks (2004); Foundations of Algorithms (1996, 1998, 2003, 2010, 2015), which has been translated into three languages; Probabilistic Methods for Financial and Marketing Informatics (2007); and Probabilistic Methods for Bioinformatics (2009). His approach to textbook writing is distinct in that he introduces a concept or methodology with simple examples, and then provides the theoretical underpinning. As a result, his books have the reputation for making difficult material easy to understand without sacrificing scientific rigor. Xia Jiang is an associate professor in the Department of Biomedical Informatics at the University of Pittsburgh School of Medicine.