Machine Learning and Artificial Intelligence with Industrial Applications: From Big Data to Small Data (Management and Industrial Engineering) - Softcover

 
9783030910082: Machine Learning and Artificial Intelligence with Industrial Applications: From Big Data to Small Data (Management and Industrial Engineering)
Softcover
ISBN 10: 3030910083 ISBN 13: 9783030910082
Verlag: Springer, 2023

Inhaltsangabe

This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.

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Über die Autorin bzw. den Autor

Diego Carou is an Assistant Professor at the Univeristy of Vigo. He received his PhD degree in industrial engineering from the National University of Distance Education (UNED) in 2013. He has international postdoctoral experience in manufacturing process at several European universities. His interests include Industry 4.0, manufacturing and sustainability.  

Antonio Sartal is a distinguished researcher in the Department of Business Management and Marketing at the University of Vigo, Spain. He managed the Department of R&D of a food multinational for the past ten years, until he joined REDE, a multidisciplinary research group working on technology management and organizational innovation. His research interests include the intersection of lean thinking, innovation management and Industry 4.0 technologies.   


J. Paulo Davim is a Full Professor at the University of Aveiro,Portugal. He is also distinguished as honorary professor in several universities/colleges in China, India and Spain. He has more than 30 years of teaching and research experience in Manufacturing, Materials, Mechanical and Industrial Engineering, with special emphasis in Machining & Tribology. He has also interest in Management, Engineering Education and Higher Education for Sustainability.

Von der hinteren Coverseite

This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.


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Verlag
Springer
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
3030910083
ISBN 13 
9783030910082
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
224
Herausgeber
Carou Diego, Sartal Antonio, Davim J. Paulo
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

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9783030910051: Machine Learning and Artificial Intelligence with Industrial Applications: From Big Data to Small Data (Management and Industrial Engineering)

Vorgestellte Ausgabe

ISBN 10:  3030910059 ISBN 13:  9783030910051
Verlag: Springer, 2022
Hardcover