Details
Machine Learning and Artificial Intelligence with Industrial Applications
From Big Data to Small DataManagement and Industrial Engineering
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160,49 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 11.03.2022 |
| ISBN/EAN: | 9783030910068 |
| Sprache: | englisch |
| Anzahl Seiten: | 209 |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<div>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.</div><div><br></div>
A Note on Big Data and Value Creation.- Modern Machine Learning: Applications and Methods.- Decision Support System Based on Deep Learning for Improving The Quality Control Task of Rifles: A Case Study In Industry 4.0.- Title: Ml & Ai Application for The Automotive Industry.- Application of Machine Learning and Big-Data Techniques to Quality Control and Food Safety In The Industrial Production of Food and Beverages.
<div><b>Diego Carou</b> 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. </div><div><br></div><div><b>Antonio Sartal</b> 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. </div><div><br></div><div><b><br></b></div><div><b>J. Paulo Davim</b> 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.</div>
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.<div><br></div>
Lists the tools used in machine learning and their benefits when used in facilities Presents a wide range of applications and case studies for different industrial sectors Explains the most popular algorithms clearly and succinctly without calculus or matrix/vector algebra
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