| Description |
1 online resource |
|
text txt rdacontent |
|
computer c rdamedia |
|
online resource cr rdacarrier |
| Bibliography |
Includes bibliographical references and index. |
| Note |
Description based on online resource; title from digital title page (viewed on February 17, 2023). |
| Summary |
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 Based on the authors' recently published and previously unpublished results, this book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations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 dataanalysis 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. -- Provided by publisher. |
| Subject |
Big data -- Mathematics.
|
|
Big data -- Mathematical models.
|
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Données volumineuses -- Mathématiques.
|
|
Données volumineuses -- Modèles mathématiques.
|
| Genre/Form |
Electronic books.
|
| Added Author |
Wang, Haiyan, author.
|
| Other Form: |
Print version: 9780443186806 |
|
Print version: 0443186790 9780443186790 (OCoLC)1329423931 |
| ISBN |
0443186804 electronic book |
|
9780443186806 (electronic bk.) |
|
0443186790 |
|
9780443186790 |
| Standard No. |
AU@ 000073485918 |
|
UKMGB 020802980 |
|
AU@ 000074354864 |
|
