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Synopsis
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.
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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.
From the Back Cover
<p>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.</p><p><br></p><p>Content</p><p>• Data Analytics</p><p>• Data and Relations</p>• Data Preprocessing<p></p><p>• Data Visualization</p><p>• Correlation</p><p>• Regression</p><p>• Forecasting</p><p>• Classification</p><p>• Clustering</p><p><br></p><p>Target Groups</p><p></p><ul><li>Students of computer science, mathematics and engineering<br></li><li>Data analytics practitioners<br></li></ul><p></p><p><br></p><p>The Author</p><p>Thomas A. Runkler is Principal Research Scientist at Siemens Corporate Technology and Professor for Computer Science at the Technical University of Munich.</p><p><br></p>
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