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undergraduate thesis
Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa
Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2020. urn:nbn:hr:235:072803
Vugić, Martin
University of Zagreb
Faculty of Mechanical Engineering and Naval Architecture

Institutional repository: Repository of Faculty of Mechanical Engineering and Naval Architecture University of Zagreb

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Vugić, M. (2020). Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:235:072803

Vugić, Martin. "Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa." Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2020. https://urn.nsk.hr/urn:nbn:hr:235:072803

Vugić, Martin. "Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa." Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2020. https://urn.nsk.hr/urn:nbn:hr:235:072803

Vugić, M. (2020). 'Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa', Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, accessed 17 November 2024, https://urn.nsk.hr/urn:nbn:hr:235:072803

Vugić M. Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture; 2020 [cited 2024 November 17] Available at: https://urn.nsk.hr/urn:nbn:hr:235:072803

M. Vugić, "Tehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa", Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:235:072803

Metadata
TitleTehnike dubokog učenja primjenjene kod analize prijetnji od korona virusa
Title (english)Deep learning techniques applied in coronavirus threat analysis
AuthorMartin Vugić
MentorTomislav Stipančić (mentor)
Committee memberZoran Kunica (predsjednik povjerenstva)
Committee memberDanko Brezak (član povjerenstva)
Committee memberTomislav Stipančić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
Zagreb
Defense date and country2020-09-24, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Precision Mechanical Engineering
Abstract
Kako tehnologija napreduje, a globalna populacija raste, raste i količina podataka i informacija koje svakodnevno stvaramo. Njihovo sortiranje, skupljanje i analiziranje može biti poprilično težak i mukotrpan zadatak. Jedna od najzastupljenijih i najnovijih grana strojnog učenja, duboko učenje (deep learning) upravo se bavi tom problematikom. Duboko učenje se temelji na predstavljanju podataka složenim algoritmima na visokom stupnju apstrakcije do kojih se dolazi slijedom stečenih nelinearnih transformacija. Metode dubokog učenja svoju primjenu pronalaze u važnim područjima kao što su: umjetna inteligencija, obrade prirodnog jezika, u bioinformatici i sl., no u okviru ovog rada, koristit ćemo je u analiziranju i predviđanju trendova bolesti zastupljenom korona virusom ili skraćeno COVID-19, uz stečene podatke i statistike u programskom jeziku Python.
Abstract (english)
As technology advances and the world’s population grows, so does the amount of data we create every day. Collecting, sorting and analyzing them can be quite a difficult and demanding task. One of the most common and newest branches of machine learning, deep learning, deals with this kind of issues. Deep learning is based on the presentation of complex data algorithms at a high degree of abstraction which are given by learned nonlinear transformations. Deep learning methods find their application in important areas such as artificial intelligence, natural language processing, bioinformatics, etc., but in this paper, we will use it to analyze and predict trends with acquired data and statistics for disease aquired by corona virus, or shortened COVID-19 in the Python programming language.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:235:072803
Study programmeTitle: Mechanical Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-09-24 11:44:23