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Pregled bibliografske jedinice broj: 1038858

Interoperability of Machine Learning Services: A Use Case


Andročec, Darko; Tikvica, Andrea
Interoperability of Machine Learning Services: A Use Case // Books of Proceedings of the 49thInternational Scientific Conference on Economic and Social DevelopmentDevelopment –"Building Resilient Society" / Dukic, Darko ; Studzieniecki, Tomasz ; Grzinic, Jasmina (ur.).
Zagreb: VADEA, 2019. str. 106-113 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Interoperability of Machine Learning Services: A Use Case

Autori
Andročec, Darko ; Tikvica, Andrea

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Books of Proceedings of the 49thInternational Scientific Conference on Economic and Social DevelopmentDevelopment –"Building Resilient Society" / Dukic, Darko ; Studzieniecki, Tomasz ; Grzinic, Jasmina - Zagreb : VADEA, 2019, 106-113

Skup
49th International Scientific Conference on Economic and Social Development: Building Resilient Society

Mjesto i datum
Zagreb, Hrvatska, 13.12.2019. - 14.12.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
cloud ; interoperability ; machine learning ; services

Sažetak
Machine learning has become very popular because the supporting infrastructure is now available for reasonable price and most companies have big data sources for solving problems in a high-dimensional space. There are many business use cases that show successful application of machine learning methods. However, machine learning methods are complex, so many cloud providers (e.g. Google, Amazon, Microsoft) have recently started to offer different machine learning services. SMEs often want to use multiple machine learning services of different cloud providers. In this work, we present current state-of-the-art of machine learning services interoperability research. Additionally, a real use case is implemented to show how SMEs can use two machine learning services of two different cloud providers in one application. Concretely, a web application has been developed by implementing machine learning services of two different cloud service providers. The following services are used within the practical example: text detection with the support of the Google Cloud Platform and text translation services with the support of Microsoft Azure. The idea of the practical example is to show the interoperability of the mentioned platforms.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet organizacije i informatike, Varaždin

Profili:

Avatar Url Darko Andročec (autor)


Citiraj ovu publikaciju:

Andročec, Darko; Tikvica, Andrea
Interoperability of Machine Learning Services: A Use Case // Books of Proceedings of the 49thInternational Scientific Conference on Economic and Social DevelopmentDevelopment –"Building Resilient Society" / Dukic, Darko ; Studzieniecki, Tomasz ; Grzinic, Jasmina (ur.).
Zagreb: VADEA, 2019. str. 106-113 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Andročec, D. & Tikvica, A. (2019) Interoperability of Machine Learning Services: A Use Case. U: Dukic, D., Studzieniecki, T. & Grzinic, J. (ur.)Books of Proceedings of the 49thInternational Scientific Conference on Economic and Social DevelopmentDevelopment –"Building Resilient Society".
@article{article, author = {Andro\v{c}ec, Darko and Tikvica, Andrea}, year = {2019}, pages = {106-113}, keywords = {cloud, interoperability, machine learning, services}, title = {Interoperability of Machine Learning Services: A Use Case}, keyword = {cloud, interoperability, machine learning, services}, publisher = {VADEA}, publisherplace = {Zagreb, Hrvatska} }
@article{article, author = {Andro\v{c}ec, Darko and Tikvica, Andrea}, year = {2019}, pages = {106-113}, keywords = {cloud, interoperability, machine learning, services}, title = {Interoperability of Machine Learning Services: A Use Case}, keyword = {cloud, interoperability, machine learning, services}, publisher = {VADEA}, publisherplace = {Zagreb, Hrvatska} }

Časopis indeksira:


  • HeinOnline





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