Strojno učenje kao alat za zaključivanje

Gregorić, Marin

undergraduate thesis

Strojno učenje kao alat za zaključivanje

Zagreb: University of Zagreb, University of Zagreb, Faculty of Humanities and Social Sciences, 2019. urn:nbn:hr:131:590439

Gregorić, Marin

University of Zagreb
Faculty of Humanities and Social Sciences
Department of information and Communication sciences

Cite this document

APA 6th Edition

Gregorić, M. (2019). Strojno učenje kao alat za zaključivanje (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Humanities and Social Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:131:590439

MLA 8th Edition

Gregorić, Marin. "Strojno učenje kao alat za zaključivanje." Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, 2019. https://urn.nsk.hr/urn:nbn:hr:131:590439

Chicago 17th Edition

Gregorić, Marin. "Strojno učenje kao alat za zaključivanje." Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, 2019. https://urn.nsk.hr/urn:nbn:hr:131:590439

Harvard

Gregorić, M. (2019). 'Strojno učenje kao alat za zaključivanje', Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, accessed 07 February 2025, https://urn.nsk.hr/urn:nbn:hr:131:590439

Vancouver

Gregorić M. Strojno učenje kao alat za zaključivanje [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Humanities and Social Sciences; 2019 [cited 2025 February 07] Available at: https://urn.nsk.hr/urn:nbn:hr:131:590439

IEEE

M. Gregorić, "Strojno učenje kao alat za zaključivanje", Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:131:590439

Cite this item: https://urn.nsk.hr/urn:nbn:hr:131:590439

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Metadata

Title	Strojno učenje kao alat za zaključivanje
Title (english)	Machine learning as prediction tool
Author	Marin Gregorić
Mentor	Sanja Seljan (mentor)
Committee member	Ivan Dunđer (predsjednik povjerenstva)
Committee member	Marko Pavlovski (član povjerenstva)
Committee member	Sanja Seljan (član povjerenstva)
Granter	University of Zagreb Faculty of Humanities and Social Sciences (Department of information and Communication sciences) Zagreb
Defense date and country	2019-09-24, Croatia
Scientific / art field, discipline and subdiscipline	SOCIAL SCIENCES Information and Communication Sciences
Abstract	Strojno učenje postaje sve češći alat u većini znanstvenih disciplina. Ovaj tekst pokušava objasniti strojno učenje i njegove osnovne koncepte kroz klasifikaciju sustava strojnog učenja i kroz objašnjenja najkorištenijih algoritama. Također prikazuje kako stvoriti sustav strojnog učenja za klasifikaciju korištenjem klasifikatora K najbližih susjeda, logističke regresije te linearnog i RBF stroja potpornih vektora. Također, objašnjeno je kako interpretirati rezultate najkorištenijih metoda za evaluaciju sustava strojnog učenja.
Abstract (english)	Machine learning is becoming a more prevelant tool in most science fields. This text tries to explain machine learning and its basic concepts through classification of machine learning systems and through explanations of most used algorithms. It is also presents how to create a machine learning system for classification using K- nearest neighbors classifier, logistic regression, and linear and RBF kernel support vector machines. Also, it is shown how to interpret results of most used methods for evaluating machine learning systems.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:131:590439
Study programme	Title: Information Sciences Study programme type: university Study level: undergraduate Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informacijskih znanosti (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informacijskih znanosti)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Repository	ODRAZ
Created on	2019-10-30 12:27:10