Editors:
- Discusses recently developed, innovative machine learning algorithms for applications in industry
- Presents the state of the art in machine learning algorithms for a global industrial scenario
- Written by respected experts in the field
Part of the book series: Studies in Computational Intelligence (SCI, volume 907)
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Table of contents (17 chapters)
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Front Matter
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Natural Language Processing
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Front Matter
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Computer Vision
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Front Matter
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Data Analysis and Prediction
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Front Matter
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Decision Making System
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Front Matter
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About this book
The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.
Editors and Affiliations
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School of Computer Science and Engineering, National Institute of Science and Technology (Autonomous), Berhampur, India
Santosh Kumar Das, Shom Prasad Das
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Department of Information Technology, Techno India College of Technology, Kolkata, India
Nilanjan Dey
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Founder and Head of the Egyptian Scientific Research Group (SRGE), Information Technology Department, Cairo University, Faculty of Computer and Artificial Intelligence, Giza, Egypt
Aboul-Ella Hassanien
Bibliographic Information
Book Title: Machine Learning Algorithms for Industrial Applications
Editors: Santosh Kumar Das, Shom Prasad Das, Nilanjan Dey, Aboul-Ella Hassanien
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-50641-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-50640-7Published: 19 July 2020
Softcover ISBN: 978-3-030-50643-8Published: 20 July 2021
eBook ISBN: 978-3-030-50641-4Published: 18 July 2020
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVII, 315
Number of Illustrations: 47 b/w illustrations, 117 illustrations in colour
Industry Sectors: Aerospace, Automotive, Biotechnology, Chemical Manufacturing, Consumer Packaged Goods, Electronics, Energy, Utilities & Environment, Engineering, Finance, Business & Banking, Health & Hospitals, IT & Software, Law, Materials & Steel, Oil, Gas & Geosciences, Pharma, Telecommunications