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Artificial Intelligence Big Data And Data Science In Statistics Challenges And Solutions In Environmetrics The Natural Sciences And Technology Ansgar Steland

  • SKU: BELL-47278216
Artificial Intelligence Big Data And Data Science In Statistics Challenges And Solutions In Environmetrics The Natural Sciences And Technology Ansgar Steland
$ 31.00 $ 45.00 (-31%)

5.0

18 reviews

Artificial Intelligence Big Data And Data Science In Statistics Challenges And Solutions In Environmetrics The Natural Sciences And Technology Ansgar Steland instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 11 MB
Pages: 377
Author: Ansgar Steland, Kwok-Leung Tsui
ISBN: 9783031071546, 3031071549
Language: English
Year: 2022

Product desciption

Artificial Intelligence Big Data And Data Science In Statistics Challenges And Solutions In Environmetrics The Natural Sciences And Technology Ansgar Steland by Ansgar Steland, Kwok-leung Tsui 9783031071546, 3031071549 instant download after payment.

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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