prikaz prve stranice dokumenta Metode strojnog učenja za klasifikaciju cijena stolnih računala
  Download
PDF 1.48 MB
master's thesis
Metode strojnog učenja za klasifikaciju cijena stolnih računala
Diplomski rad
2022. urn:nbn:hr:145:479299
Menčik, Dominik
Josip Juraj Strossmayer University of Osijek
Faculty of Economics and Business in Osijek
Chair of Quantitative Methods and Informatics

Cite this document

Menčik, D. (2022). Metode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:145:479299

Menčik, Dominik. "Metode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, 2022. https://urn.nsk.hr/urn:nbn:hr:145:479299

Menčik, Dominik. "Metode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, 2022. https://urn.nsk.hr/urn:nbn:hr:145:479299

Menčik, D. (2022). 'Metode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, accessed 03 February 2025, https://urn.nsk.hr/urn:nbn:hr:145:479299

Menčik D. Metode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek; 2022 [cited 2025 February 03] Available at: https://urn.nsk.hr/urn:nbn:hr:145:479299

D. Menčik, "Metode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics and Business in Osijek, Osijek, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:145:479299

Please login to the repository to save this object to your list.
Metadata
TitleMetode strojnog učenja za klasifikaciju cijena stolnih računala : Diplomski rad
Title (english)Machine learning methods for classifying desktop prices : Graduate paper
AuthorDominik Menčik
MentorSlobodan Jelić (mentor)
Committee memberJosip Mesarić (predsjednik povjerenstva)
Committee memberMartina Briš Alić (član povjerenstva)
Committee memberSlobodan Jelić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Economics and Business in Osijek
(Chair of Quantitative Methods and Informatics)
Osijek
Defense date and country2022-09-20, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Economics
Business Informatics
Abstract
Metode strojnog učenja koriste se i primjenjuju godinama u raznim područjima poznatima čovjeku. Od medicine i obrazovanja sve do masovne proizvodnje i primjene u pametnim tvornicama. U ekonomiji također imamo primjera primjene umjetne inteligencije, npr. u kretanju cijena dionica, prognoziranju rizika, predviđanju cijena pojedinih proizvoda i slično. Ova primjena umjetne inteligencije je veoma česta u našem okruženju. Organizacije svakim danom pokušavaju poboljšati primjenu ove umjetne inteligencije da bi na što brži i efikasniji način predvidjele i dobile odgovore kretanja cijena u realnom vremenu. U ovome radu bit će prikazane povijesna i teoretska podloga strojnog učenja. Prikazana je i objašnjena osnovna podjela strojnog učenja te je objašnjeno duboko učenje. Objasnit će se modeli poput logičke regresije, k-najbližih susjeda i neuronskih mreža, te će se pokušati utvrditi koja je metoda najbolja prilikom predviđanja cijena računala. Za analizu i modeliranje projekta koristit će se programski alat Python.
Abstract (english)
The methods of machine learning are being used and are applied in various areas known to man. From medicine and education to mass production and application in smart factories. In economy, too, are examples of application of artificial intelligence in smart factories i.e., the fluctuation of the stock market, risk prognosis, predicting prices of certain products etc. This application of artificial intelligence is commonly used in our environment. Companies try to enhance the application of this particular AI so that they would predict and find the answers to price fluctuation in real-time more efficiently. This paper will showcase the historic and theoretic background of machine learning. Machine learning is also shown and explained on a basic level, but also deep learning will be touched upon. Models such as logistic regression, k-nearest neighbor algorithm and neural network will be described and this paper will try to find out which method is most suited for predicting PC prices. Python, a high-level programming language, will be used for the analysis and project modelling. Keywords: machine learning, k-nearest neighbor algorithm, logistic regression, neural network, deep learning
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:145:479299
Study programmeTitle: Business economy; specializations in: Trade and logistics, Management, Logistic management , Business informatics
Course: Business informatics
Study programme type: university
Study level: graduate
Academic / professional title: Magistar/magistra ekonomije (Magistar/magistra ekonomije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-04-19 10:34:44