Data Analytics

Models and Algorithms for Intelligent Data Analysis

  • Thomas A. Runkler

Table of contents

  1. Front Matter
    Pages i-xii
  2. Thomas A. Runkler
    Pages 1-3
  3. Thomas A. Runkler
    Pages 5-22
  4. Thomas A. Runkler
    Pages 23-36
  5. Thomas A. Runkler
    Pages 37-58
  6. Thomas A. Runkler
    Pages 59-65
  7. Thomas A. Runkler
    Pages 67-83
  8. Thomas A. Runkler
    Pages 85-89
  9. Thomas A. Runkler
    Pages 91-109
  10. Thomas A. Runkler
    Pages 111-132
  11. Back Matter
    Pages 133-150

About this book


This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.


• Data Analytics

• Data and Relations

• Data Preprocessing

• Data Visualization

• Correlation

• Regression

• Forecasting

• Classification

• Clustering

Target Groups

  • Students of computer science, mathematics and engineering
  • Data analytics practitioners

The Author

Thomas A. Runkler is Principal Research Scientist at Siemens Corporate Technology and Professor for Computer Science at the Technical University of Munich.


data mining knowledge discovery algorithms forecasting classification clustering business intelligence machine learning deep learning

Authors and affiliations

  • Thomas A. Runkler
    • 1
  1. 1.MünchenGermany

Bibliographic information

  • DOI
  • Copyright Information Springer Fachmedien Wiesbaden 2016
  • Publisher Name Springer Vieweg, Wiesbaden
  • eBook Packages Computer Science
  • Print ISBN 978-3-658-14074-8
  • Online ISBN 978-3-658-14075-5
  • Buy this book on publisher's site