Data Analytics
Models and Algorithms for Intelligent Data Analysis
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Beschreibung
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.ContentData Analytics - Data and Relations - Data Preprocessing - Data Visualization - Correlation - Regression - Forecasting - Classification - ClusteringTarget GroupsStudents of data analytics for engineering, computer science and math Practitioners working on data analytics projectsThe AuthorThomas Runkler is doing researchat Siemens Corporate Technology in Munich and teaching data analytics and machine learning at the Technical University of Munich.
This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It covers data preprocessing, visualization, correlation, regression, forecasting, classification, and clustering. 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. The text is designed for undergraduate and graduate courses on data analytics for engineering, computer science, and math students. It is also suitable for practitioners working on data analytics projects. This book has been used for more than ten years in numerous courses at the Technical University of Munich, Germany, 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.
A comprehensive introduction Enabling the reader to design and implement data analytics solutions for real-world applications Successfully used for more than 10 years Includes supplementary material: sn.pub/extras Includes supplementary material: sn.pub/extras
Autor*in
Thomas A. Runkler
Themen in »Data Analytics«
Classification business intelligence data mining knowledge discovery machine learning data structures