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Automating Real-Time Data Analysis with Machine Learning Algorithms

  • Sonali P. Bhoite
  • , Satendra Singh
  • , Preeti Naval
  • , M. V. Panduranga Rao
  • , Bharat Bhushan
  • , G. Indira

Research output: Chapter in Book/ReportConference contributionpeer-review

Abstract

Device getting-to-know algorithms enable the automation of actual-time information analysis, permitting agencies to behave on well-timed insights and optimize selection-making. By leveraging predictive models, companies can increase customized services, optimize operations, and obtain a competitive area. This paper discusses how device learning algorithms can automate real-time facts evaluation and the ways such algorithms can be used to uncover developments, locate anomalies, and enhance models. Moreover, the paper explores how applying device mastering algorithms can boost accuracy and efficiency in data evaluation, in addition to providing businesses with new opportunities for innovation.

Original languageAmerican English
Title of host publication2023 3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350319125
DOIs
StateIndexed - 2023
Externally publishedYes
Event3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023 - Bangalore, India
Duration: 29 Dec 202331 Dec 2023

Publication series

Name2023 3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

Conference

Conference3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023
Country/TerritoryIndia
CityBangalore
Period29/12/2331/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Algorithms
  • Anomalies
  • Applying
  • Leveraging
  • Operations

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