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Data science for mathematicians /
Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
Chapman & Hall/CRC,
[2021]
|
| Edición: | First edition. |
| Colección: | CRC Press/Chapman and Hall Handbooks in Mathematics
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Data science for mathematicians / |c edited by Nathan Carter. |
| 250 | |a First edition. | ||
| 264 | 1 | |a Boca Raton, FL : |b Chapman & Hall/CRC, |c [2021] | |
| 300 | |a 1 online resource : |b illustrations (black and white) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 0 | |a CRC Press/Chapman and Hall Handbooks in Mathematics | |
| 504 | |a Includes bibliographical references. | ||
| 505 | 0 | |a Programming with data / Sean Raleigh -- Linear algebra / Jeffery Leader -- Basic statistics / David White -- Clustering / Amy S. Wagaman -- Operations research / Alice Paul and Susan Martonosi -- Dimensionality reduction / Sofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, and Henry Kvinge -- Machine learning / Mahesh Agarwal, Nathan Carter, and David Oury -- Deep learning / Samuel S. Watson -- Topological data analysis / Henry Adams, Johnathan Bush, Joshua Mirth. | |
| 520 | |a Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them. | ||
| 545 | 0 | |a Nathan Carter is a professor at Bentley University. | |
| 588 | 0 | |a Online resource; title from digital title page (viewed on December 30, 2020). | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Mathematical analysis. | |
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Big data |x Mathematics. | |
| 650 | 2 | |a Data Mining | |
| 650 | 6 | |a Analyse mathématique. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Données volumineuses |x Mathématiques. | |
| 650 | 7 | |a MATHEMATICS |x General. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a Mathematical statistics |2 fast | |
| 650 | 7 | |a Mathematical analysis |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 655 | 7 | |a handbooks. |2 aat | |
| 655 | 7 | |a Handbooks and manuals. |2 lcgft | |
| 655 | 7 | |a Guides et manuels. |2 rvmgf | |
| 700 | 1 | |a Carter, Nathan C., |e editor. | |
| 758 | |i has work: |a Data science for mathematicians (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGhcdm4bh4Hy7Dcf3GDPBd |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Carter, Nathan. |t Data Science for Mathematicians. |d Milton : CRC Press LLC, ©2020 |z 9780367027056 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6309040 |z Texto completo |
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