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Artificial intelligence, big data an...

Steland, Ansgar.

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Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence, big data and data science in statistics/ edited by Ansgar Steland, Kwok-Leung Tsui.
Reminder of title:	challenges and solutions in environmetrics, the natural sciences and technology /
other author:	Steland, Ansgar.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	viii, 376 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-031-07155-3
ISBN:	9783031071553

Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology /
Artificial intelligence, big data and data science in statisticschallenges and solutions in environmetrics, the natural sciences and technology /[electronic resource] :edited by Ansgar Steland, Kwok-Leung Tsui. - Cham :Springer International Publishing :2022. - viii, 376 p. :ill., digital ;24 cm.

This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book's expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.

ISBN: 9783031071553

Standard No.: 10.1007/978-3-031-07155-3doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: Q335

Dewey Class. No.: 006.3

Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology /
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300 $a viii, 376 p. : $b ill., digital ; $c 24 cm.
520 $a This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book's expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
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