Mathematical Foundations of Data Science (Texts in Computer Science)
Language: English
Published by Springer, 2024
- Softcover
- New

Seller: Biblios, frankfurt am main, hessen, GermanyBiblios
AbeBooks seller since September 10, 2024
Condition: New
US$ 104.62
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- Title
- Mathematical Foundations of Data Science (Texts in Computer Science)
- Author
- Hrycej, Tomas; Bermeitinger, Bernhard; Cetto, Matthias; Handschuh, Siegfried
- Publisher
- Springer
- Publication year
- 2024
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3031190769
- ISBN 13
- 9783031190766
- Series
- Book 75 of 83: Texts in Computer Science
Topics and features:
- Focuses on approaches supported by mathematical arguments, rather than sole computing experiences
- Investigates conditions under which numerical algorithms used in data science operate, and what performance can be expected from them
- Considers key data science problems: problem formulation including optimality measure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithms
- Examines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problem
- Addresses the trade-off between model size and volume of data available for its identification and its consequences for model parametrization
- Investigates the mathematical principles involves with natural language processing and computer vision
- Keeps subject coverage intentionally compact, focusing on key issues of each topic to encourage full comprehension of the entire book
Although this core textbook aims directly at students of computer science and/or data science, it will be of real appeal, too, to researchers in the field who want to gain a proper understanding of the mathematical foundations “beyond” the sole computing experience.
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Biblios
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