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dc.contributor.authorLeland, David S.
dc.contributor.authorDubiel, Sean W.
dc.date.accessioned2020-03-11T15:10:52Z
dc.date.available2020-03-11T15:10:52Z
dc.date.issued2018-04
dc.identifier.urihttp://digital.library.wisc.edu/1793/79923
dc.descriptionColor poster with text, bar graphs, and images.en_US
dc.description.abstractGoogle'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.sponsorshipUniversity of Wisconsin--Eau Claire Office of Research and Sponsored Programs.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesUSGZE AS589;
dc.subjectPostersen_US
dc.subjectCryptocurrencyen_US
dc.subjectBitcoinen_US
dc.subjectEconomicsen_US
dc.titleUsing Machine Learning and Sentiment Analysis to Predict Cryptocurrency Price Fluctuationsen_US
dc.typePresentationen_US


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  • Student Research Day
    Posters of collaborative student/faculty research presented at Student Research Day

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