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undergraduate thesis
Grupiranje korisnika algoritmima strojnog učenja
2022. urn:nbn:hr:179:210048
Jukić, Marija
University of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Department of Electronics and Computing

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Jukić, M. (2022). Grupiranje korisnika algoritmima strojnog učenja (Undergraduate thesis). Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:179:210048

Jukić, Marija. "Grupiranje korisnika algoritmima strojnog učenja." Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:210048

Jukić, Marija. "Grupiranje korisnika algoritmima strojnog učenja." Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:210048

Jukić, M. (2022). 'Grupiranje korisnika algoritmima strojnog učenja', Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, accessed 15 November 2024, https://urn.nsk.hr/urn:nbn:hr:179:210048

Jukić M. Grupiranje korisnika algoritmima strojnog učenja [Undergraduate thesis]. Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture; 2022 [cited 2024 November 15] Available at: https://urn.nsk.hr/urn:nbn:hr:179:210048

M. Jukić, "Grupiranje korisnika algoritmima strojnog učenja", Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:179:210048

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Metadata
TitleGrupiranje korisnika algoritmima strojnog učenja
Title (english)User clustering using machine learning algorithms
AuthorMarija Jukić
MentorLjiljana Šerić (mentor)
GranterUniversity of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
(Department of Electronics and Computing)
Split
Defense date and country2022-09-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Kroz ovaj završni rad obrađena je tema grupiranja podataka, jednog od oblika nenadziranog strojnog učenja. U radu su opisani načini rada različitih algoritama za grupiranje s fokusom na algoritam k sredine te načine provjere kvalitete modela. Opisana je analiza i obrada podataka te priprema potrebnih podataka za izradu modela. Izrađen je model strojnog učenja koji automatski grupira korisnike GPS-a u tri grupe i pružena je evaluacija točnosti modela. U praktičnom dijelu izrade rada, korišten je programski jezik python. Za analizu, obradu i pripremu podataka korištena je python biblioteka pandas, te za izradu i procjenu modela korišten je scikit-learn.
Abstract (english)
Throughout this final thesis, the clustering of data, a type of unsupervised machine learning, was analyzed. The methods of use for different clustering algorithms were described, with a focus on the k-means algorithm and model quality assurance. Analysis, preparation, and processing of necessary data for the creation of the model were also detailed. A machine learning model, which groups GPS data into three distinct clusters, was built and its accuracy tested. The programming language used for the practical portion of this thesis was python. Python's library pandas was used to prepare the data. Lastly, scikit-learn was used to create and evaluate the model.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:179:210048
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to authenticated users
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Created on2023-05-18 11:15:10