Web aplikacija za raspoznavanje raspoloženja pjesama s usluge Spotify koristeći strojno učenje

undergraduate thesis

• Title (english): Web application for recognizing the mood of songs from Spotify service
• Author: Katarina Bošnjak
• Mentor: Alan Jović (mentor)
• Committee member: Alan Jović (predsjednik povjerenstva)
• Committee member: Nikolina Frid (član povjerenstva)
• Committee member: Igor Stančin (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2022-07-01, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U radu je opisana implementacija tri različita algoritma strojnog učenja: neuronska mreža, slučajna šuma i stroj potpornih vektora. Uspoređene su njihove performanse. Izabrana je neuronska mreža koja je ukomponirana u web aplikaciju te korisnicima otkriva raspoloženja odabranih pjesama.

Abstract (english)

The paper describes the implementation of three different machine learning algorithms: neural network, random forest and support vector machine. Their performances were compared. A neural network was chosen, which was then integrated into the web application that calculates the moods of the selected songs and presents them to the user.

• Keywords: Neuronska mreža; slučajna šuma; stroj potpornih vektora; strojno učenje
• Keywords (english): Neural network; random forest; support vector machine; machine learning
• Language: croatian
• URN:NBN: urn:nbn:hr:168:835357
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-15 09:48:55