Industry 4.0, AI, and data science: research trends and challenges

"The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere...

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Bibliographic Details
Other Authors: Bali Vikram (Editor), Banerjee, Kakoli (Editor), Kumar, Narendra (Editor), Gour, Sanjay (Editor), Chawla, Sunil Kumar (Editor)
Format: Electronic eBook
Language:English
Published: Boca Raton ; London ; New York CRC Press 2022
Edition:First edition
Series:Demystifying technologies for computational excellence: moving towards society 5.0
Subjects:
Online Access:DE-M347
DE-355
DE-739
Volltext
Summary:"The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed. Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.
Item Description:Includes bibliographical references and index
Physical Description:1 Online-Ressource (xix, 261 Seiten) Illustrationen
ISBN:9781003097181
DOI:10.1201/9781003097181

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