Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases.Applications range from datamining programs that discover general rules in large data sets, to information filtering systems that automatically learn users' interests.

To solve problems computers require intelligence. Learning is central to intelligence. As intelligence requires knowledge, it is necessary for the computers to acquire knowledge. Machine learning serves this purpose.

Machine learning refers to a system capable of acquiring and integrating the knowledge automatically. The capability of the systems to learn from experience, training, analytical observation, and other means, results in a system that can continuously self-improve and thereby exhibit efficiency and effectiveness.

The book covers fundamental topics as Data Mining, Decision Tree, Supervised Learning , Reinforcement Learning
Bayesian Decision Theory, Computational Learning Theory, Artificial Neural Network, Instance-Based Learning etc.

This book provides a single source introduction to the field.