Primarily intended for the undergraduate and postgraduate students of computer science and engineering, this text bridges knowledge gaps in artificial intelligence and machine learning.

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.