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Description

An essential roadmap to the application of computational statistics in contemporary data science
In Computational Statistics in Data Science, a team of distinguished mathematicians and statisticians delivers an expert compilation of concepts, theories, techniques, and practices in computational statistics for readers who seek a single, standalone sourcebook on statistics in contemporary data science. The book contains multiple sections devoted to key, specific areas in computational statistics, offering modern and accessible presentations of up-to-date techniques.
Computational Statistics in Data Science provides complimentary access to finalized entries in the Wiley StatsRef: Statistics Reference Online compendium. Readers will also find: A thorough introduction to computational statistics relevant and accessible to practitioners and researchers in a variety of data-intensive areas Comprehensive explorations of active topics in statistics, including big data, data stream processing, quantitative visualization, and deep learning
Perfect for researchers and scholars working in any field requiring intermediate and advanced computational statistics techniques, Computational Statistics in Data Science will also earn a place in the libraries of scholars researching and developing computational data-scientific technologies and statistical graphics.
Pages
672 pages
Collection
n.c
Parution
2022-03-23
Marque
Wiley
EAN papier
9781119561071
EAN PDF
9781119561057

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
672
Taille du fichier
26798 Ko
Prix
225,72 €
EAN EPUB
9781119561088

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
672
Taille du fichier
30290 Ko
Prix
225,72 €

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