PHI Learning, 06.03.2014 - 368 Seiten
Primarily intended for the undergraduate and postgraduate students of computer science and engineering, this text bridges the gaps in knowledge of the seemingly difficult areas of artificial intelligence and machine learning. This book promises to provide the most number of case studies and worked out examples than any other of its genre. The text is written in a highly interactive manner which makes for an avid reading. More into the text, the contents are well placed that it takes off from the introduction to AI, which is followed by heuristics searching and game playing. The machine learning section begins with the basis of learning, and the various association rule learning algorithms. Various types of learning like, reinforced, supervised, unsupervised and statistical are also included with numerous case studies and application exercises. The well explained algorithms and pseudo codes for each topic make this book useful for students. KEY FEATURES • Includes Case studies for each machine learning algorithm • Incorporates day to day examples and pictorial representations for a deeper understanding of the subject • Helps students to create programs easily

Autoren-Profil (2014)

Chandra S.S., Vinod VINOD CHANDRA S.S., PhD, is Director, Computer Centre, University of Kerala, Thiruvananthapuram. He is leading many e-Governance projects associated with universities and Kerala Government. With more than a decade of teaching experience in various engineering colleges in Kerala, he has published more than fifty research papers on a wide range of topics in Machine Intelligence. He has also authored three established books. He is a reviewer of many international journals and chair of many International conferences. His research areas include Machine learning algorithms and Computational biology. Hareendran S., Anand ANAND HAREENDRAN S., is associated with Department of Computer Science and Engineering, College of Engineering, Kulathoor, Sreekaryam, Trivandrum. He has presented several research papers in both national and international conferences in the field of machine learning. His research area is performance evaluation of machine learning algorithms

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