Guide to Intelligent Data Analysis

In 2010 Springer published the book a Guide to Intelligent Data Analysis with some excellent topics and features, such as:

  • 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
  • Supplies further tools and information at the associated website:

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