Review
“The book is especially suitable as a course support (especially as each chapter also ends with a set of exercises), but also as introductory material for master or PhD students that are new to the data analytics domain, as they can obtain a quick overview.” (Ruxandra Stoean, zbMATH 1373.68007, 2017)
Product Description
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.
From the Back Cover
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.
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.
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