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Title:Trgovanje kriptovalut z okrepitvenim učenjem : diplomsko delo
Authors:ID Reher, Gašper (Author)
ID Karakatič, Sašo (Mentor) More about this mentor... New window
Files:.pdf UN_Reher_Gasper_2020.pdf (1,66 MB)
MD5: 1EB238A07C5A327E2BC2C2564D1B32A6
PID: 20.500.12556/dkum/79ac15ca-2385-496d-9cf4-98b09f283453
 
.zip UN_Reher_Gasper_2020.zip (19,64 KB)
MD5: BCAFB25CD1652E92D134584D3A32742F
PID: 20.500.12556/dkum/161e8c52-a81c-4631-80c9-cb02ff4c7036
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu se bom seznanil in preizkusil okrepitveno učenje na časovnih podatkih, natančneje na trgovanju s kriptovalutami. V okviru naloge bom naredil teoretičen pregled okrepitvenega učenja, ogrodji okrepitvenega učenja in pregled knjižnic, ki že obstajajo na področju okrepitvenega učenja ter trgovanja s kriptovalutami. Praktični cilj diplomskega dela pa je izdelava programa, ki se bo na podlagi zgodovinskih vrednosti kriptovalut, naučil, kako trgovati z njimi, tako da zagotovi velik dobiček.
Keywords:Okrepitveno učenje, kriptovalute, Python, umetna inteligenca
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[G. Reher]
Year of publishing:2020
Number of pages:VI, 43 f.
PID:20.500.12556/DKUM-76964 New window
UDC:004.8(043.2)
COBISS.SI-ID:39007491 New window
NUK URN:URN:SI:UM:DK:DYW6CCFR
Publication date in DKUM:03.11.2020
Views:3419
Downloads:253
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-ND 4.0, Creative Commons Attribution-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nd/4.0/
Description:Under the NoDerivatives Creative Commons license one can take a work released under this license and re-distribute it, but it cannot be shared with others in adapted form, and credit must be provided to the author.
Licensing start date:04.08.2020

Secondary language

Language:English
Title:Trading cryptocurrencies with reinforcement learning
Abstract:In my diploma work I will get acquainted with reinforcement learning and test it on historical data, more specifically on cryptocurrency trading. As part of the assignment, I will provide a theoretical overview of reinforcement learning, reinforcement learning frameworks, and an overview of libraries that already exist in the area of reinforcement learning and cryptocurrency trading. The practical aim of the diploma thesis is to create a program that, based on the historical values of cryptocurrencies, will learn how to trade them so as to generate large profits.
Keywords:Reinforcement learning, cryptocurrencies, Python, artificial intelligent


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