This book provides a hands-on instructional approach to many data analysis techniques, and explains how use them to solve real world problems.
"Guide to Intelligent Data Analysis" provides a hands-on instructional
approach to many data analysis techniques, and explains how these are
used to solve real world data analysis problems. In contrast to many
other books it focuses more on the process itself instead of individual
methods. The book is complemented by practical sections based on the open
source tools R and KNIME and teaching material is available from the book's
website at www.idaguide.net.
Topics and features:
- Guides the reader through the process of data analysis, following the
interdependent steps of project understanding, data understanding, data
preparation, modeling, and deployment and monitoring;
- Equips the reader with the necessary information in order to obtain
hands-on experience of the topics under discussion;
- Provides a review of the basics of classical statistics that support
and justify many data analysis methods, and a glossary of statistical
terms;
- Includes numerous examples using R and KNIME, together with appendices
introducing the open source software;
- Integrates illustrations and case-study-style examples to support
pedagogical exposition;
- Teaching material and further information are available at the associated
website: www.idaguide.net.
This practical and systematic textbook/reference for graduate and advanced
undergraduate students is also essential reading for all professionals who
face data analysis problems. Moreover, it is a book to be used following
one's exploration of it.
The book is available directly from Springer:
www.springer.com/computer/ai/book/978-1-84882-259-7
and, of course, at your favorite e-Bookseller
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