000			02078nam a22003015i 4500
001			91217
005			20231026103816.0
010			_a978-3-031-07155-3 _dcompra
090			_a91217
100			_a20231023d2022 k||y0pory50 ba
101	0		_aeng
102			_aCH
200	1		_aArtificial intelligence, big data and data science in statistics _bDocumento eletrónico _echallenges and solutions in environmetrics, the natural sciences and technology _fedited by Ansgar Steland, Kwok-Leung Tsui
210			_aCham _cSpringer International Publishing _cSpringer _d2022
215			_aVIII, 376 p. _cil.
303			_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.
606			_aStatistics
606			_aArtificial intelligence _xData processing
606			_aMachine learning
606			_aBig data
680			_aQA276-280
702	1		_aSteland _bAnsgar _4340
702	1		_aTsui _bKwok-Leung _4340
801		0	_aPT _gRPC
856	4		_uhttps://doi.org/10.1007/978-3-031-07155-3
942			_2lcc _cF _n0