Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction
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.
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Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction
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.
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Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction

Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction

by Thomas A. Runkler
Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction
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Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction

Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction

by Thomas A. Runkler

Overview

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.

Product Details

ISBN-13: 9783658459512
Publisher: Springer Vieweg
Publication date: 12/21/2024
Sold by: Barnes & Noble
Format: eBook
File size: 13 MB
Note: This product may take a few minutes to download.

About 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.

Table of Contents

Introduction.- Data and Relations.- Data Preprocessing.- Data Visualization.- Correlation.- Regression.- Forecasting.- Classification.- Clustering.

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