Using Machine Learning and Sentiment Analysis to Predict Cryptocurrency Price Fluctuations
| dc.contributor.author | Leland, David S. | |
| dc.contributor.author | Dubiel, Sean W. | |
| dc.date.accessioned | 2020-03-11T15:10:52Z | |
| dc.date.available | 2020-03-11T15:10:52Z | |
| dc.date.issued | 2018-04 | |
| dc.description | Color poster with text, bar graphs, and images. | en_US |
| dc.description.abstract | Google's Machine Learning Library, Tensorflow, and the Python programming language were applied to predict cryptocurrency (e.g. Bitcoin) prices using technical indicators and quantified sentiment analysis. | en_US |
| dc.description.sponsorship | University of Wisconsin--Eau Claire Office of Research and Sponsored Programs. | en_US |
| dc.identifier.uri | http://digital.library.wisc.edu/1793/79923 | |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | USGZE AS589; | |
| dc.subject | Posters | en_US |
| dc.subject | Cryptocurrency | en_US |
| dc.subject | Bitcoin | en_US |
| dc.subject | Economics | en_US |
| dc.title | Using Machine Learning and Sentiment Analysis to Predict Cryptocurrency Price Fluctuations | en_US |
| dc.type | Presentation | en_US |
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