Uporaba strojnega učenja v programskem inženirstvu

magistrsko delo

Ivan Tomić (Author), Peter Kokol (Mentor)

Abstract

V magistrskem delu je predstavljena uporaba strojnega učenja v programskem inženirstvu. Strojno učenje nam omogoča pridobivanje dragocenih informacij in ustvarjanje napovednih modelov, ki prispevajo k razvoju številnih rešitev na različnih področjih. Eno od teh področji je tudi programsko inženirstvo, kjer nam lahko strojno učenje pomaga izboljšati učinkovitost, pohitriti razvoj in zmanjšati število napak. Z vse večjim številom aplikacij, ki vključujejo strojno učenje pa narašča tudi potreba po razvoju bolj učinkovitih postopkov pri izdelavi programske opreme za te namene. Zato smo v tem magistrskem delu raziskali kako oblikovati postopke za razvoj programske opreme, ki temelji na strojnem učenju, ter predstavili sodobna orodja strojnega učenja za optimalen razvoj AI aplikacij.

Keywords

strojno učenje;programsko inženirstvo;optimizacija razvojnih procesov;orodja umetne inteligence;magistrske naloge;

Data

Language:	Slovenian
Year of publishing:	2024
Typology:	2.09 - Master's Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[I. Tomić]
UDC:	004.85:004.41(043.2)
COBISS:	224206595
Views:	0
Downloads:	16
Average score:	0 (0 votes)
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Other data

Secondary language:	English
Secondary title:	Software engineering for machine learning
Secondary abstract:	The master's thesis presents challenges in software engineering for machine learning. Machine learning enables us to obtain valuable information and create predictive models that contribute to the development of various solutions in different fields. One of these fields is also software engineering, where machine learning can help us improve efficiency, speed up development and reduce the number of errors. With an increasing number of applications incorporating machine learning, the need to develop more efficient software development processes is also increasing. Therefore, in this master's thesis, we explored how to design procedures for the development of software based on machine learning and presented modern machine learning tools for the optimal development of AI applications.
Secondary keywords:	machine learning;software engineering;optimization of development processes;Artificial Intelligence Tools;master's theses;
Type (COBISS):	Master's thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages:	1 spletni vir (1 datoteka PDF (VII, 57 f.))
ID:	24819379