Gridiron Genius: Using Neural Networks to Predict College Football
dc.contributor.author | Boll, Luke | |
dc.contributor.advisor | McCormick, Jason | |
dc.date.accessioned | 2023-06-08T20:20:42Z | |
dc.date.available | 2023-06-08T20:20:42Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/176935 | |
dc.description.abstract | This project aims to revolutionize college football game predictions by utilizing neural networks and deep learning technologies. This project is able to forecast college football games with a high degree of accuracy by utilizing enormous historical game data. By training the system with a variety of factors such as team statistics and home-field advantage, this model can provide reliable insights and predictions for the most passionate college football fans. | |
dc.subject | neural networks | |
dc.subject | machine learning | |
dc.subject | college football | |
dc.title | Gridiron Genius: Using Neural Networks to Predict College Football | |
dc.type | Project | |
dc.subject.hlbtoplevel | Engineering | |
dc.contributor.affiliationum | Computer Science and Aerospace Engineering | |
dc.contributor.affiliationumcampus | Ann Arbor | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/176935/1/Luke_Boll_Honors_Capstone_Report_-_Luke_Boll.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/176935/2/Luke_boll_capstone_poster_-_Luke_Boll.pdf | |
dc.identifier.doi | https://dx.doi.org/10.7302/7671 | |
dc.working.doi | 10.7302/7671 | en |
dc.owningcollname | Honors Program, The College of Engineering |
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