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© 2020

Data Analytics

Models and Algorithms for Intelligent Data Analysis

Textbook

Table of contents

  1. Front Matter
    Pages i-xii
  2. Thomas A. Runkler
    Pages 1-4
  3. Thomas A. Runkler
    Pages 5-22
  4. Thomas A. Runkler
    Pages 23-36
  5. Thomas A. Runkler
    Pages 37-59
  6. Thomas A. Runkler
    Pages 61-68
  7. Thomas A. Runkler
    Pages 69-87
  8. Thomas A. Runkler
    Pages 89-94
  9. Thomas A. Runkler
    Pages 95-115
  10. Thomas A. Runkler
    Pages 117-139
  11. Back Matter
    Pages 141-161

About this book

Introduction

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.


Content

• 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.


Keywords

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

Authors and affiliations

  1. 1.MünchenGermany

About the authors

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

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