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Springer Vieweg - IT & Informatik - Datenbanken | Data Analytics - Models and Algorithms for Intelligent Data Analysis

Data Analytics

Models and Algorithms for Intelligent Data Analysis

Runkler, Thomas A.

2012, X, 137 p. 66 illus.

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  • A comprehensive introduction

This book is a comprehensive introduction to the methods and algorithms and approaches 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 numerous courses at the Technical University of Munich, in short courses at several other universities, and in tutorials at scientific conferences. 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 data analytics for engineering, computer science and math 

Practitioners working on data analytics projects

The Author

Thomas Runkler is doing research at Siemens Corporate Technology in Munich and teaching data analytics and machine learning at the Technical University of Munich.

Content Level » Lower undergraduate

Keywords » Classification - business intelligence - data mining - knowledge discovery - machine learning

Related subjects » Datenbanken - Grundlagen

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