Publication: Cloud computing architecture for high-volume ML-based solutions
Дата
2019
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Аннотация
© 2019 IEEE A large number of modern projects use machine learning technology to perform a variety of business calculations. There are two main ways to integrate machine-learning models into the logic of industrial applications. The first way is to rewrite models from the data analysis language (for example R or Python) to the industrial development language (for example Java, Go or Scala). The second way is to equip models with a web-interface and integrate it into the calculation. In this article, we explore the second method. A deployment architecture for machine learning in the clouds is proposed. The possibilities of the proposed scheme for scaling are described. Examples of practical use of the proposed architecture for organizing data storage with compression are also given.
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Cloud computing architecture for high-volume ML-based solutions / Rovnyagin, M.M. [et al.] // Proceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019. - 2019. - P. 315-318. - 10.1109/EIConRus.2019.8656765
URI
https://www.doi.org/10.1109/EIConRus.2019.8656765
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https://www.scopus.com/record/display.uri?eid=2-s2.0-85063543228&origin=resultslist
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https://openrepository.mephi.ru/handle/123456789/16728