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Machine Learning Based on Cloud Solutions

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dc.contributor.author Chmielecki, Przemysław
dc.date.accessioned 2019-08-12T08:31:50Z
dc.date.available 2019-08-12T08:31:50Z
dc.date.issued 2019
dc.identifier.citation Edukacja – Technika – Informatyka nr 1(27)/2019, s. 132–138 pl_PL.UTF-8
dc.identifier.issn 2080-9069
dc.identifier.uri http://repozytorium.ur.edu.pl/handle/item/4816
dc.description.abstract Cognition is a domain of thinking creatures, isn't it? Based on that computers cannot learn anything more than was in the initial data feed. In this article, I just want to defend that nowadays technical solutions can break this rule. The aim of this article is to provide a short technical overview what Machine Learning (ML), Artificial Intelligence (AI) and Neural Networks (NN) were before in the area of standalone gigantic servers, and how do they look now in Cloud Computing (CC) times. The ML paradigm is not any more reserved for big enterprises only but now is available for single internet user. I just want to present AWS and Azure, as the biggest CC providers, functionalities and potential usage of such Cognitive Services (CS) in current internet services. The great example is for instance bot usage instead of diving deep in the FAQ on the company website or digging into the corporate wiki. Another big area is graphics analysis and sound or text recognition. Those are only examples of predefined CC functions ready for use right now in the public cloud. pl_PL.UTF-8
dc.language.iso eng pl_PL.UTF-8
dc.publisher Wydawnictwo Uniwersytetu Rzeszowskiego pl_PL.UTF-8
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 Międzynarodowe *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Machine Learning pl_PL.UTF-8
dc.subject Artificial Intelligence pl_PL.UTF-8
dc.subject Neural Networks pl_PL.UTF-8
dc.subject Cloud Computing pl_PL.UTF-8
dc.subject Cognitive Services pl_PL.UTF-8
dc.subject AWS pl_PL.UTF-8
dc.subject Azure pl_PL.UTF-8
dc.title Machine Learning Based on Cloud Solutions pl_PL.UTF-8
dc.type article pl_PL.UTF-8
dc.identifier.doi 10.15584/eti.2019.1.17
dc.identifier.eissn 2450-9221


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