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This book includes numerous case studies and worked out examples. The text begins with an introduction to AI; this is followed by discussion of heuristics searching and game playing. The machine learning section begins with the basis of learning, before moving on to the various association rule learning algorithms. Types of learning, such as reinforced, supervised, unsupervised and statistical are also included, with numerous case studies and application exercises. The algorithms and pseudo codes for each topic make this book particularly 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.
- Helps students to easily create programmes.
Pages | 368 |
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Dimensions | 235 x 178 |
Date Published | 30 May 2014 |
Publisher | PHI Learning |
Subject/s | Computer science   Learning   |
Anand Hareendran S., is associated with Department of Computer Science and Engineering, College of Engineering, Kulathoor, Sreekaryam, Trivandrum, India. 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