Runkler, Thomas A.
Data Analytics Models and Algorithms for Intelligent Data Analysis / [electronic resource] : by Thomas A. Runkler. - 2nd ed. 2016. - XII, 150 p. 66 illus. online resource.
Data Analytics -- Data and Relations -- Data Preprocessing -- Data Visualization -- Correlation -- Regression -- Forecasting -- Classification -- Clustering.
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.
9783658140755
10.1007/978-3-658-14075-5 doi
Computer science.
Data structures (Computer science).
Data mining.
Computer Science.
Data Mining and Knowledge Discovery.
Data Structures.
QA76.9.D343
006.312
Data Analytics Models and Algorithms for Intelligent Data Analysis / [electronic resource] : by Thomas A. Runkler. - 2nd ed. 2016. - XII, 150 p. 66 illus. online resource.
Data Analytics -- Data and Relations -- Data Preprocessing -- Data Visualization -- Correlation -- Regression -- Forecasting -- Classification -- Clustering.
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.
9783658140755
10.1007/978-3-658-14075-5 doi
Computer science.
Data structures (Computer science).
Data mining.
Computer Science.
Data Mining and Knowledge Discovery.
Data Structures.
QA76.9.D343
006.312