Data Analytics
Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction
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Beschreibung
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. The new edition integrates themes such as Word Embeddings, Transformer Models, and generative AI among the contents and offers new exercises in addition. 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 Distinguished Key Expert at Siemens AG and Professor at the School of Computation, Information and Technology of the Technical University of Munich.
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. The new edition integrates themes such as Word Embeddings, Transformer Models, and generative AI among the contents and offers new exercises in addition. 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.
Enabling the reader to design and implement data analytics solutions for real-world applications Written by a researcher from industry with substantial experience with real-world data analytics applications Successfully used for more than 10 years in courses at the Technical University of Munich
Autor*in
Thomas A. Runkler
Themen in »Data Analytics«
data mining knowledge discovery algorithms forecasting classification clustering business intelligence machine learning deep learning
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