Overview
- Includes cutting-edge research from around the globe
- Discusses current status, trends, future directions, and opportunities
- Written for beginners, young researchers, and academics
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 401)
Included in the following conference series:
Conference proceedings info: ICMLBDA 2022.
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Table of contents (44 papers)
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Machine Learning and Big Data Analytics
Keywords
About this book
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence.
The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globeon this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning and Big Data Analytics
Book Subtitle: 2nd International Conference on Machine Learning and Big Data Analytics-ICMLBDA, IIT Patna, India, March 2022
Editors: Rajiv Misra, Rana Omer, Muttukrishnan Rajarajan, Bharadwaj Veeravalli, Nishtha Kesswani, Priyanka Mishra
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-031-15175-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-15174-3Published: 07 June 2023
Softcover ISBN: 978-3-031-15177-4Due: 29 August 2023
eBook ISBN: 978-3-031-15175-0Published: 06 June 2023
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: X, 566
Number of Illustrations: 45 b/w illustrations, 219 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Applications of Mathematics, Statistical Theory and Methods, Machine Learning, Statistics, general, Data Structures and Information Theory