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master's thesis
Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika
Zagreb: University of Zagreb, Faculty of Science, 2021. urn:nbn:hr:217:848781
Štefanić, Tin
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

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Štefanić, T. (2021). Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:848781

Štefanić, Tin. "Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika." Master's thesis, University of Zagreb, Faculty of Science, 2021. https://urn.nsk.hr/urn:nbn:hr:217:848781

Štefanić, Tin. "Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika." Master's thesis, University of Zagreb, Faculty of Science, 2021. https://urn.nsk.hr/urn:nbn:hr:217:848781

Štefanić, T. (2021). 'Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika', Master's thesis, University of Zagreb, Faculty of Science, accessed 24 August 2024, https://urn.nsk.hr/urn:nbn:hr:217:848781

Štefanić T. Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2021 [cited 2024 August 24] Available at: https://urn.nsk.hr/urn:nbn:hr:217:848781

T. Štefanić, "Arhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:217:848781

Metadata
TitleArhitekture dubokih neuronskih mreža u problemu obrade prirodnog jezika
Title (english)Architectures of deep neural networks in the problem of natural language processing
AuthorTin Štefanić
MentorLuka Grubišić (mentor)
Committee memberLuka Grubišić (predsjednik povjerenstva)
Committee memberZvonimir Bujanović (član povjerenstva)
Committee memberAndrej Dujella (član povjerenstva)
Committee memberGoran Muić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2021-09-22, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U ovom diplomskom radu obrađuju se izabrane arhitekture dubokih neuronskih mreža korištene u problemu obrade prirodnog jezika. U prvom poglavlju cilj je obraditi klasične arhitekture, rekurzivne neuronske mreže i LSTM, te njihove prednosti i mane. Zatim u idućem poglavlju se obrađuje modernija Transformer arhitektura, arhitektura koja sadrži prednosti klasičnih arhitektura, ali nema njihove mane. U trećem poglavlju su obrađene napredne pred-trenirane Transformer arhitekture, BERT i njegova nadogradnja ALBERT. Zatim u zadnjem poglavlju te arhitekture su primjenjene na problem odgovaranja na pitanja, problem na kojem su izražene mane klasičnih arhitektura.
Abstract (english)
This thesis deals with selected architectures of deep neural networks used in the problem of natural language processing. In the first chapter, the goal is to deal with classical architectures, recurrent neural networks and LSTM, and their advantages and disadvantages. Then, in the next chapter, we discuss the modern Transformer architecture, an architecture that possesses the advantages of classical architectures, but doesn’t share their disadvantages (e.g. it is easier to use parallel algorithms and it allows for transfer learning). The third chapter deals with the advanced pre-trained Transformer architecture, BERT and its upgrade ALBERT. Then, in the last chapter, these architectures are applied to a question answering problem, a problem on which the flaws of classical architectures are expressed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:848781
Study programmeTitle: Computer Science and Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra računarstva i matematike (magistar/magistra računarstva i matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-11-08 12:54:39