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Title:Razvoj grafičnega vmesnika za ogrodje NiaAML : diplomsko delo
Authors:ID Rant, Aljaž (Author)
ID Fister, Iztok (Mentor) More about this mentor... New window
ID Hliš, Tilen (Comentor)
Files:.pdf VS_Rant_Aljaz_2025.pdf (2,60 MB)
MD5: 7113016EC22E46C9D210AF0EE2FBFCE2
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu predstavljamo razvoj grafičnega uporabniškega vmesnika za ogrodje NiaAML, ki je ogrodje za samodejno strojno učenje, implementirano v programskem jeziku Python, zasnovano na algoritmih po vzorih iz narave. Cilj diplomskega dela je približati uporabo ogrodja tudi uporabnikom brez programerskega znanja ter jim omogočiti preprosto konfiguracijo in zagon optimizacijskih procesov. Delo vključuje teoretični pregled področja, zasnovo in implementacijo vmesnika ter evalvacijo delovanja.
Keywords:samodejno strojno učenje, uporabniški vmesnik, ogrodje NiaAML, Python, klasifikacijski cevovod
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[A. Rant]
Year of publishing:2025
Number of pages:1 spletni vir (1 datoteka PDF (X, 42 str.))
PID:20.500.12556/DKUM-94807 New window
UDC:004.5:004.85(043.2)
COBISS.SI-ID:260314883 New window
Publication date in DKUM:23.09.2025
Views:250
Downloads:42
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:27.08.2025

Secondary language

Language:English
Title:Development of the graphical interface for the NiaAML framework
Abstract:In this thesis, we present the development of a graphical user interface for the NiaAML framework, which is a framework for automated machine learning implemented in the Python programming language, based on nature-inspired algorithms. The aim of the thesis is to make the framework accessible to users without programming knowledge and enable them to easily configure and run optimization processes. The thesis includes a theoretical overview of the field, the design and implementation of the interface, and an evaluation of its performance.
Keywords:automatic machine learning, user interface, NiaAML framework, Python, classification pipeline


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