The book describes the basics of machine learning principles and algorithms that are used in data mining and is intended for students of computer science, researchers who need to adapt various algorithms for particular data mining tasks, and for education of sophisticated users of machine learning and data mining tools.

Machine learning has exhibited tremendous progress in the last two decades. Numerous systems for machine learning are nowadays available and the number of their applications in various fields, such as industry, medicine, economics, ecology, finance, and many others, is rapidly growing. Machine learning is used for data analysis and knowledge discovery in databases, data mining, automatic generation of knowledge bases for expert systems, game playing, text classification and text mining, automatic recognition of speech, handwriting, images, etc.

The basic principle of machine learning is modeling of available data. Results of various machine learning systems may be rules, functions, relations, equation systems, probability distributions and other knowledge representations. The obtained "knowledge" aims to explain the data and can be used for forecasting, diagnostics, control, validation, and simulations.