Dynamic Distributed and Parallel Machine Learning algorithms for big data mining processing

PurposeThis work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems such as P2P networks, clusters, clouds computing or other technologies.Design/methodology/approachIn the age of Big Data, all compa...

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Veröffentlicht in:	Data technologies and applications Jg. 56; H. 4; S. 558 - 601
1. Verfasser:	Djafri, Laouni
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bingley Emerald Publishing Limited 23.08.2022 Emerald Group Publishing Limited
Schlagworte:	Activity Units Algorithms Architecture Artificial Intelligence Big Data Classification Cloud computing Companies Computer architecture Computer networks Data analysis Data mining Data processing Data science Datasets Information retrieval Information sources Internet of Things Knowledge Learning Processes Machine learning Motion Parallel processing Probability Random sampling Sampling Sampling methods Shared learning System effectiveness Talking Teaching Methods Validity Velocity Work Writers Big data mining Big data platforms Distributed and parallel processing Statistical sampling Machine learning Map-reduce
ISSN:	2514-9288, 2514-9318
Online-Zugang:	Volltext
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