Advances in Distributed Computing and Machine Learning Proceedings of ICADCML 2021 / edited by Jyoti Prakash Sahoo, Asis Kumar Tripathy, Manoranjan Mohanty, Kuan-Ching Li, Ajit Kumar Nayak.

Advances in Distributed Computing and Machine Learning Proceedings of ICADCML 2021 /

This book presents recent advances in the field of scalable distributed computing including state-of-the-art research in the field of Cloud Computing, the Internet of Things (IoT), and Blockchain in distributed environments along with applications and findings in broad areas including Data Analytics...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Sahoo, Jyoti Prakash (Editor), Tripathy, Asis Kumar (Editor), Mohanty, Manoranjan (Editor), Li, Kuan-Ching (Editor), Nayak, Ajit Kumar (Editor)
Format: Electronic eBook
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2022.
Edition:1st ed. 2022.
Series:Lecture notes in networks and systems ; 302.
Subjects:
Computational intelligence.
Artificial intelligence.
Machine learning.
Blockchains (Databases)
Internet of things.
Online Access: Full text (Wentworth users only)
Description
Summary:This book presents recent advances in the field of scalable distributed computing including state-of-the-art research in the field of Cloud Computing, the Internet of Things (IoT), and Blockchain in distributed environments along with applications and findings in broad areas including Data Analytics, AI, and Machine Learning to address complex real-world problems. It features selected high-quality research papers from the 2nd International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2021), organized by the Department of Computer Science and Information Technology, Institute of Technical Education and Research(ITER), Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India.
Physical Description:XXX, 513 pages 332 illustrations, 184 illustrations in color : online resource.
ISBN:9789811648076
ISSN:2367-3389 ;
DOI:10.1007/978-981-16-4807-6

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