Mathematical Methods in Data Science
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72 581 Ft (69 125 Ft + 5% VAT)
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72 581 Ft
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Product details:
- Publisher Elsevier Science
- Date of Publication 11 January 2023
- ISBN 9780443186790
- Binding Paperback
- No. of pages258 pages
- Size 228x152 mm
- Weight 410 g
- Language English 428
Categories
Long description:
Mathematical Methods in Data Science covers a broad range of mathematical tools used in data science, including calculus, linear algebra, optimization, network analysis, probability and differential equations. Based on the authors' recently published and previously unpublished results, this book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data
analysis and prediction. With data science being used in virtually every aspect of our society, the book includes examples and problems arising in data science and the clear explanation of advanced mathematical concepts, especially data-driven differential equations, making it accessible to researchers and graduate students in mathematics and data science.
Table of Contents:
1. Linear Algebra
2. Probability
3. Calculus and Optimization
4. Network Analysis
5. Ordinary Differential Equations
6. Partial Differential Equations
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