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master's thesis
Raspodijeljeno duboko učenje u računarstvu u magli
2020. urn:nbn:hr:168:788092
Kotarski, Dominik
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Kotarski, D. (2020). Raspodijeljeno duboko učenje u računarstvu u magli (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:788092

Kotarski, Dominik. "Raspodijeljeno duboko učenje u računarstvu u magli." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:788092

Kotarski, Dominik. "Raspodijeljeno duboko učenje u računarstvu u magli." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:788092

Kotarski, D. (2020). 'Raspodijeljeno duboko učenje u računarstvu u magli', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 22 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:788092

Kotarski D. Raspodijeljeno duboko učenje u računarstvu u magli [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 April 22] Available at: https://urn.nsk.hr/urn:nbn:hr:168:788092

D. Kotarski, "Raspodijeljeno duboko učenje u računarstvu u magli", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:788092

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Metadata
TitleRaspodijeljeno duboko učenje u računarstvu u magli
Title (english)Distributed Deep Learning in Fog Computing
AuthorDominik Kotarski
MentorIgor Čavrak (mentor)
Committee memberIgor Čavrak (predsjednik povjerenstva)
Committee memberDanko Basch (član povjerenstva)
Committee memberIvana Bosnić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad bavi se integracijom koncepta dubokog učenja kao pripadnika paradigme strojnog učenja u nadolazeće raspodijeljene sustave u magli. Obrađuje se tema računarstva u magli i njegovih prednosti i nedostataka, poglavito u odnosu na računarstvo u oblaku. Dan je pregled koncepta dubokog učenja. Naposljetku, dani su i komentirani rezultati ispitivanja koncepta horizontalne raspodijeljene inferencije u dubokom učenju.
Abstract (english)
This thesis is concerned with integration of deep learning, as a member of machine learning paradigm, into the oncoming fog computing systems. Fog computing is compared to cloud computing, noting any and all differences and highlighting benefits and challenges. An overview of deep learning is given. Finally, results of testing the concept of horizontal distribution in deep learning inference are provided and commented on.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:788092
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
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Created on2023-01-13 12:44:10