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Machine Learning and Data Mining: Methods and Applications
 
 

Machine Learning and Data Mining: Methods and Applications (Hardcover)

by Ryszad S. Michalski (Editor), Ivan Bratko (Editor), Miroslav Kubat (Editor) "The field of machine learning was conceived nearly four decades ago with the bold objective to develop computational methods that would implement various forms of..." (more)
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Product Description

Product Description
Master the new computational tools to get the most out of your information system.

This practical guide, the first to clearly outline the situation for the benefit of engineers and scientists, provides a straightforward introduction to basic machine learning and data mining methods, covering the analysis of numerical, text, and sound data.

From the Back Cover
Being able to extract meaningful patterns and strategic knowledge from large stores of information held electronically is increasingly a challenge facing the business and science worlds. In response, methods are being developed for discovering patterns and general rules from the information in databases, data warehouses and document information systems. This book is the first major text dedicated to issues at the intersection of machine learning and data mining – two interrelated fields that provide the foundations for these methods. Written by a team of international experts Machine Learning and Data Mining presents an exciting contribution addressing the new challenge. It provides an introduction to basic methods and its coverage spans the analysis of numerical data, text, images and sound. Most impressively, the book describes applications across a wide spectrum of real world problems, in domains such as engineering, control, biology, medicine and music

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The field of machine learning was conceived nearly four decades ago with the bold objective to develop computational methods that would implement various forms of learning, in particular mechanisms capable of inducing knowledge from examples or data. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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