Computational Statistics in Data Science

[FaridKhan]

Computational Statistics in Data Science

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[center]English | 2022 | ISBN: ‎ 1119561078, 978-1119561071 | 674 pages | True PDF | 27.32 MB[/center]

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[b]An essential roadmap to the application of computational statistics in contemporary data science[/b]
In[i]Computational Statistics in Data Science[/i], 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.
[i]Computational Statistics in Data Science[/i] provides complimentary access to finalized entries in the[i]Wiley StatsRef: Statistics Reference Online[/i] compendium. Readers will also find:

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[*]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
[/list]

Perfect for researchers and scholars working in any field requiring intermediate and advanced computational statistics techniques,[i]Computational Statistics in Data Science[/i]will also earn a place in the libraries of scholars researching and developing computational data-scientific technologies and statistical graphics.

[b]An essential roadmap to the application of computational statistics in contemporary data science[/b]
In [i]Computational Statistics in Data Science[/i], 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.
[i]Computational Statistics in Data Science[/i] provides complimentary access to finalized entries in the [i]Wiley StatsRef: Statistics Reference Online[/i] compendium. Readers will also find:
[list]
[*]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
[/list]

Perfect for researchers and scholars working in any field requiring intermediate and advanced computational statistics techniques, [i]Computational Statistics in Data Science [/i]will also earn a place in the libraries of scholars researching and developing computational data-scientific technologies and statistical graphics.

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