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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Carter, Nathan C. (Editor )
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:
Mathematical analysis.
Mathematical statistics.
Data mining.
Big data > Mathematics.
Data Mining
Analyse mathématique.
Exploration de données (Informatique)
Données volumineuses > Mathématiques.
MATHEMATICS > General.
MATHEMATICS > Applied.
Mathematical statistics
Mathematical analysis
Data mining
handbooks.
Handbooks and manuals.
Guides et manuels.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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