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Data Analytics

Models and Algorithms for Intelligent Data Analysis

  • Textbook
  • © 2020

Overview

Authors:
  1. Thomas A. Runkler

    1. München, Germany

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  • A comprehensive introduction
  • Enabling the reader to design and implement data analytics solutions for real-world applications
  • Written by a researcher from industry with substantial experience with real-world data analytics applications
  • Successfully used for more than 10 years in courses at the Technical University of Munich

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xii
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  2. Introduction

    • Thomas A. Runkler
    Pages 1-4

  3. Data and Relations

    • Thomas A. Runkler
    Pages 5-22

  4. Data Preprocessing

    • Thomas A. Runkler
    Pages 23-36

  5. Data Visualization

    • Thomas A. Runkler
    Pages 37-59

  6. Correlation

    • Thomas A. Runkler
    Pages 61-68

  7. Regression

    • Thomas A. Runkler
    Pages 69-87

  8. Forecasting

    • Thomas A. Runkler
    Pages 89-94

  9. Classification

    • Thomas A. Runkler
    Pages 95-115

  10. Clustering

    • Thomas A. Runkler
    Pages 117-139

  11. Back Matter

    Pages 141-161
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Keywords

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.

Authors and Affiliations

  • München, Germany

    Thomas A. Runkler

About the author

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

Bibliographic Information

  • Book Title: Data Analytics

  • Book Subtitle: Models and Algorithms for Intelligent Data Analysis

  • Authors: Thomas A. Runkler

  • DOI: https://doi.org/10.1007/978-3-658-29779-4

  • Publisher: Springer Vieweg Wiesbaden

  • eBook Packages: Computer Science and Engineering (German Language)

  • Copyright Information: Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020

  • Softcover ISBN: 978-3-658-29778-7Published: 14 May 2020

  • eBook ISBN: 978-3-658-29779-4Published: 13 May 2020

  • Edition Number: 3

  • Number of Pages: XII, 161

  • Number of Illustrations: 72 b/w illustrations

  • Topics: Data Mining and Knowledge Discovery, Data Structures and Information Theory

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