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Sklop video predstavitev problemov v podatkovnem rudarjenju
ID JAKLJEVIČ, SAŠO (Author), ID Zupan, Blaž (Mentor) More about this mentor... This link opens in a new window

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PID: 20.500.12556/rul/1a57067f-ed71-43b1-8d3c-d713faa5a2da

Abstract
S porastom količine podatkov je področje podatkovnega rudarjenja vse bolj priljubljeno. Da bi uporabo orodij strojnega učenja, vizualizacij podatkov in iskanja zakonitosti v podatkih omogočili čim večji skupini uporabnikov, se v zadnjem času pojavljajo programi, ki uporabljajo tehnike vizualnega programiranja. S temi programi je moč postopke podatkovne analitike snovati vizualno, brez uporabe posebnih programskih jezikov. Primeri takih orodij so RapidMiner, KNIME, Weka in Orange. Za ta orodja v nalogi pregledamo, na kakšen način preko kratkih videov predstavljajo svojo funkcionalnost. Končni izdelek naše naloge sta nato dva motivacijska videa, ki predstavita primera podatkovnega rudarjenja in uporabo orodja Orange ter z njim nekaj izbranih tehnik vizualizacije podatkov in napovednih modelov.

Language:Slovenian
Keywords:podatkovno rudarjenje, video predstavitev, izobraževalne vsebine, programska orodja
Work type:Bachelor thesis/paper
Organization:FRI - Faculty of Computer and Information Science
Year:2017
PID:20.500.12556/RUL-89079 This link opens in a new window
Publication date in RUL:13.02.2017
Views:1536
Downloads:390
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Secondary language

Language:English
Title:Batch of video presentation of challanges in data mining
Abstract:
As we store more and more data, Data mining field grows increasingly popular. To enable usage of machine learning tools, visualizations and knowledge discovery in data to the widest possible audience, computer applications that leverage techniques of visual programing stated to appear. These applications enable visual structuring of data analytic processes without the usage of special programming languages. Examples of such tools are RapidMiner, KNIME, Weka and Orange. In the scope of this paper we look at how functionalities of these tools are presented. End result of the paper are two motivational videos, that present examples of data mining and usage of data mining application called Orange. Examples will show a few chosen techniques of visualization and prediction models.

Keywords:data mining, video presentation, educational content, software

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