Carmen-Ionela ROTUNĂ1,2, Mihail DUMITRACHE1,3, Ionuț-Eugen SANDU1,4
1 National Institute for Research and Development in Informatics – ICI Bucharest
2 Politehnica University of Bucharest
3 University of Bucharest – Faculty of Letters
4 „Lucian Blaga“ University of Sibiu
firstname.lastname@example.org, email@example.com, firstname.lastname@example.org
Abstract: Artificial Intelligence and Machine Learning have made exponential progress in the last decade with a significant technological impact both on individual users and organizations in multiple domains of activity. The capabilities of AI applications, which were built using dedicated algorithms, have increased continuously, which enabled them to perform sophisticated processing tasks. Language, computer vision, autonomous driving, robotics, and automated application monitoring, which have been core problems in AI ever since 1950, have reached a new technological peak nowadays. This study aims to overview and classify Machine Learning algorithms based on certain predefined criteria. This classification can be used for the development of complex ML automation applications where the repetitive tasks performed by users would be taken over by the AI applications.
Keywords: AI, Machine Learning, supervised learning, reinforcement learning, automation.
CITE THIS PAPER AS:
Carmen-Ionela ROTUNĂ, Mihail DUMITRACHE, Ionuț-Eugen SANDU, Assessment of Machine Learning algorithms for automated monitoring, Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 32(3), pp. 73-84, 2022. https://doi.org/10.33436/v32i3y202206