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Produktbild: Data Science | Matthias Plaue
Produktbild: Data Science | Matthias Plaue

Data Science

An Introduction to Statistics and Machine Learning

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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.

Inhaltsverzeichnis

Preface. - Part I Basics. - 1 Elements of data organization. - 2 Descriptive statistics. - Part II Stochastics. - 3 Probability theory. - 4 Inferential statistics. - 5 Multivariate statistics. - Part III Machine learning. - 6 Supervised machine learning. - 7 Unsupervised machine learning. - 8 Applications of machine learning. - Appendix. - A Exercises with answers. - B Mathematical preliminaries. - Supplementary literature. - Index.

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Produktdetails

Erscheinungsdatum
31. August 2023
Sprache
englisch
Auflage
1st ed. 2023
Seitenanzahl
361
Dateigröße
15,39 MB
Reihe
Computer Science
Autor/Autorin
Matthias Plaue
Kopierschutz
mit Wasserzeichen versehen
Produktart
EBOOK
Dateiformat
PDF
ISBN
9783662678824

Portrait

Matthias Plaue

Matthias Plaue is a versatile researcher with a background in mathematical physics. He has explored diverse domains, spanning from relativity theory to pedestrian dynamics. As a data scientist, he develops algorithms for data analysis and artificial intelligence, tailored to support strategic decision-making. In addition to his professional pursuits, he has devoted considerable time to mentoring students, imparting a deep understanding of mathematics and its practical application in tackling complex problems across the fields of science, technology, and engineering.

Pressestimmen


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)


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