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MARC 21

Artificial Intelligence, Big Data and Data Science in Statistics: Challenges and Solutions in Environmetrics, the Natural Sciences and Technology /
Tag	Description
020	$a9783031071553$9978-3-031-07155-3
082	$a519.5$223
099	$aOnline resource: Springer
245	$aArtificial Intelligence, Big Data and Data Science in Statistics$h EBook$bChallenges and Solutions in Environmetrics, the Natural Sciences and Technology /$cedited by Ansgar Steland, Kwok-Leung Tsui.
250	$a1st ed. 2022.
260	$aCham :$bSpringer International Publishing :$bImprint: Springer,$c2022.
300	$aVIII, 376 p. 1 illus.$bonline resource.
336	$atext$btxt$2rdacontent
337	$acomputer$bc$2rdamedia
338	$aonline resource$bcr$2rdacarrier
520	$aThis 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.
533	$a Digital reproduction.-
533	$b Cham :
533	$c Springer International Publishing,
533	$d 2022. -
533	$nMode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format.
538	$aOnline access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
700	$aSteland, Ansgar.$eeditor.$4edt$4http://id.loc.gov/vocabulary/relators/edt
700	$aTsui, Kwok-Leung.$eeditor.$4edt$4http://id.loc.gov/vocabulary/relators/edt
710	$aSpringerLink (Online service)
856	$uhttps://doi.org/10.1007/978-3-031-07155-3