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Data Analytics Models and Algorithms for Intelligent Data Analysis

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. T...

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Bibliographic Details
Main Author: Runkler, Thomas A.
Format: eBook
Language:English
Published: Wiesbaden Springer Fachmedien Wiesbaden 2020, 2020
Edition:3rd ed. 2020
Subjects:
Data Structures And Information Theory
Data Mining
Information Theory
Data Structures (computer Science)
Data Mining And Knowledge Discovery
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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505 0 |a Introduction -- Data and Relations -- Data Preprocessing -- Data Visualization -- Correlation -- Regression -- Forecasting -- Classification -- Clustering 
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520 |a 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 atSiemens Corporate Technology and Professor for Computer Science at the Technical University of Munich 

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