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Computational Statistics in Data Science
Computational Statistics in Data Science
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- More about Computational Statistics in Data Science
Computational Statistics in Data Science is a comprehensive roadmap to applying computational statistics in contemporary data science, featuring concepts, theories, techniques, and practices from distinguished mathematicians and statisticians. It offers modern and accessible presentations of up-to-date techniques, with complimentary access to Wiley StatsRef: Statistics Reference Online compendium.
Format: Hardback
Length: 672 pages
Publication date: 21 April 2022
Publisher: John Wiley and Sons Ltd
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.
Weight: 1270g
Dimension: 250 x 177 x 41 (mm)
ISBN-13: 9781119561071
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