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master's thesis
Integracija modela strojnog učenja u REST API serversku aplikaciju
Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. urn:nbn:hr:179:303718
Huljaj, Martina
University of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Department of Electronics and Computing

Institutional repository: Repository of the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture

Cite this document

Huljaj, M. (2022). Integracija modela strojnog učenja u REST API serversku aplikaciju (Master's thesis). Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:179:303718

Huljaj, Martina. "Integracija modela strojnog učenja u REST API serversku aplikaciju." Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:303718

Huljaj, Martina. "Integracija modela strojnog učenja u REST API serversku aplikaciju." Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:303718

Huljaj, M. (2022). 'Integracija modela strojnog učenja u REST API serversku aplikaciju', Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, accessed 11 July 2024, https://urn.nsk.hr/urn:nbn:hr:179:303718

Huljaj M. Integracija modela strojnog učenja u REST API serversku aplikaciju [Master's thesis]. Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture; 2022 [cited 2024 July 11] Available at: https://urn.nsk.hr/urn:nbn:hr:179:303718

M. Huljaj, "Integracija modela strojnog učenja u REST API serversku aplikaciju", Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:179:303718

Metadata
TitleIntegracija modela strojnog učenja u REST API serversku aplikaciju
Title (english)Integration of a machine learning model into a RESTfull API server application
AuthorMartina Huljaj
MentorMario Čagalj https://orcid.org/0000-0003-0235-7436 (mentor)
GranterUniversity of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
(Department of Electronics and Computing)
Split
Defense date and country2022-09-16, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U okviru ovog diplomskog rada obrađuje se polje strojnog učenja te njegova primjena u svakodnevnom životu. Teoretski dio rada ukratko pojašnjava koncepte umjetne inteligencije i strojnog učenja, te predstavlja tehnologije korištene za razvoj aplikacije koja nadalje približava te koncepte korisnicima kroz njihovu praktičnu primjenu. Praktični rad obuhvaća izradu modela strojnog učenja u Pythonu pomoću biblioteke TensorFlow i Keras API-ja. Kroz razvoj modela pojašnjavaju se problemi na koje se nailazi pri rješavanju konkretnog problema strojnog učenja, te kako se može pristupiti njihovom rješavanju. Trenirani model se nadalje integrira u mobilnu aplikaciju. Razvoj mobilne aplikacije rađen je u Flutter razvojnom okruženju. Flutter je razvojna okolina nastala 2010. godine i od tada njena popularnost samo raste. Flutter omogućava razvoj mobilnih aplikacija za Android i iOS uređaje uz pomoć bogate unaprijed definirane biblioteke widgeta. Implementacija modela strojnog učenja u mobilnu aplikaciju vrši se upotrebom Flask Api-ja. Flask je minimalistička razvojna okolina koja omogućava jednostavnu preobrazbu običnog Python koda u funkcionalnu web aplikaciju. Integracijom različitih tehnologija u jedinstvenu mobilnu aplikaciju, demonstrira se fleksibilnost te opširnost današnjih tehnologija u polju računarstva.
Abstract (english)
This diploma thesis deals with the field of machine learning and its application in everyday life. The theoretical part of the paper briefly explains the concepts of artificial intelligence and machine learning, and presents the technologies used to develop applications that further bring these concepts closer to users. Practical work includes creating a machine learning model in Python using the Tensorflow library and the Keras API. While developing the model, some problems specific to machine learning appear, which presented the opportunity to cover different approaches to their solution. The perfected and trained model is further integrated into the mobile application. The development of the mobile application was done in the Flutter framework. Flutter is a framework created in 2010 and since then its popularity has only grown. Flutter enables the development of mobile applications for Android and iOS devices with the help of a rich predefined library of widgets. The implementation of the machine learning model in the mobile application is done using the Flask Api. Flask is a minimalist framework that allows you to easily transform plain Python code into a functional web application. Integrating different technologies into a unique mobile application, demonstrates the flexibility and comprehensiveness of today's technologies in the field of computer science.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:179:303718
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 conditionsAccess restricted to authenticated users
Terms of useLicence In copyright icon
Created on2023-05-05 13:05:22