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Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges /

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics,...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Hassanien, Aboul Ella (Editor), Darwish, Ashraf (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Series:Studies in Big Data, 77
Subjects:
Engineering-Data processing.
Computational intelligence.
Big data.
Machine learning.
Data Engineering.
Computational Intelligence.
Big Data.
Machine Learning.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
Physical Description:1 online resource (XI, 648 pages 267 illustrations, 182 illustrations in color.)
ISBN:9783030593384
ISSN:2197-6511 ;
DOI:10.1007/978-3-030-59338-4