Overview
- Offers a gentle introduction into data science
- Contains numerous examples and applications
- Provides an overview of basic mathematical concepts and algorithms of data science
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About this book
This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of data science. It covers essential parts of data organization, descriptive and inferential statistics, probability theory, and machine learning. These topics are presented in a clear and mathematical sound way to help readers gain a deep and fundamental understanding. Numerous application examples based on real data are included. The book is well-suited for lecturers and students at technical universities, and offers a good introduction and overview for people who are new to the subject. Basic mathematical knowledge of calculus and linear algebra is required.
Keywords
Table of contents (8 chapters)
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Front Matter
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Basics
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Front Matter
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Stochastics
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Front Matter
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Machine learning
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Front Matter
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Back Matter
Reviews
“The book covers a wide range of topics, from basic statistical concepts to advanced machine learning algorithms. It is both deep and broad, making it a valuable resource for both beginners and experienced practitioners. Each concept is well explained and often accompanied by practical examples, which enhances understanding. The inclusion of real-world examples and applications of machine learning techniques is a major strength.” (Wael Badawy, Computing Reviews, March 1, 2024)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Data Science
Book Subtitle: An Introduction to Statistics and Machine Learning
Authors: Matthias Plaue
DOI: https://doi.org/10.1007/978-3-662-67882-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2023
Softcover ISBN: 978-3-662-67881-7Published: 01 September 2023
eBook ISBN: 978-3-662-67882-4Published: 31 August 2023
Edition Number: 1
Number of Pages: XXIV, 361
Topics: Data Structures and Information Theory, Artificial Intelligence, Statistics, general