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＜電子ブック＞
Artificial Intelligence, Big Data and Data Science in Statistics : Challenges and Solutions in Environmetrics, the Natural Sciences and Technology / edited by Ansgar Steland, Kwok-Leung Tsui

版	1st ed. 2022.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2022
本文言語	英語
大きさ	VIII, 376 p. 1 illus : online resource
著者標目	Steland, Ansgar editor Tsui, Kwok-Leung editor SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Artificial intelligence -- Data processing  全ての件名で検索 LCSH:Machine learning LCSH:Big data FREE:Statistical Theory and Methods FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Data Science FREE:Machine Learning FREE:Big Data FREE:Applied Statistics
一般注記	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 datascientists, as well as engineers and computer scientists working in related fields or applications HTTP:URL=https://doi.org/10.1007/978-3-031-07155-3

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