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Mathematical methods in data science /
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 Based on the authors' recently published and previously unpublished results, this boo...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Cambridge, MA :
Elsevier,
[2023]
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a22000007i 4500 | ||
|---|---|---|---|
| 001 | SCIDIR_on1357502790 | ||
| 003 | OCoLC | ||
| 005 | 20231120010720.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 230120s2023 ne ob 001 0 eng d | ||
| 040 | |a YDX |b eng |e rda |c YDX |d YDX |d OPELS |d EBLCP |d UKAHL |d UKMGB |d OCLCQ |d FIE |d N$T |d OCLCQ |d OCLCO | ||
| 015 | |a GBC2K2151 |2 bnb | ||
| 016 | 7 | |a 020802980 |2 Uk | |
| 019 | |a 1363837961 | ||
| 020 | |a 0443186804 |q electronic book | ||
| 020 | |a 9780443186806 |q (electronic bk.) | ||
| 020 | |z 0443186790 | ||
| 020 | |z 9780443186790 | ||
| 035 | |a (OCoLC)1357502790 |z (OCoLC)1363837961 | ||
| 050 | 4 | |a QA76.9.B45 |b R46 2023 | |
| 082 | 0 | 4 | |a 005.7 |2 23/eng/20230217 |
| 100 | 1 | |a Ren, Jingli, |e author. | |
| 245 | 1 | 0 | |a Mathematical methods in data science / |c Jingli Ren, Haiyan Wang. |
| 264 | 1 | |a Amsterdam ; |a Cambridge, MA : |b Elsevier, |c [2023] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | |a Description based on online resource; title from digital title page (viewed on February 17, 2023). | ||
| 520 | |a 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 Based on the authors' recently published and previously unpublished results, this book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations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. -- |c Provided by publisher. | ||
| 650 | 0 | |a Big data |x Mathematics. | |
| 650 | 0 | |a Big data |x Mathematical models. | |
| 650 | 6 | |a Donn�ees volumineuses |0 (CaQQLa)000284673 |x Math�ematiques. |0 (CaQQLa)201-0380112 | |
| 650 | 6 | |a Donn�ees volumineuses |0 (CaQQLa)000284673 |x Mod�eles math�ematiques. |0 (CaQQLa)201-0379082 | |
| 655 | 0 | |a Electronic books. | |
| 700 | 1 | |a Wang, Haiyan, |e author. | |
| 776 | 0 | 8 | |i Print version: |z 9780443186806 |
| 776 | 0 | 8 | |i Print version: |z 0443186790 |z 9780443186790 |w (OCoLC)1329423931 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780443186790 |z Texto completo |