
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.
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