Unsupervised Crypto Clustering with NLP
A cryptocurrency is a digital form of currency that is secured using an online ledger with cryptography. The first successful cryptocurrency was Bitcoin, which was launched in 2009 by an anonymous person under the pseudonym Satoshi Nakamoto. Similar to stocks, they can be bought and sold, and their...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/144527 |
| _version_ | 1826216044856868864 |
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| author | Zhang, Sammy |
| author2 | Durand, Frédo |
| author_facet | Durand, Frédo Zhang, Sammy |
| author_sort | Zhang, Sammy |
| collection | MIT |
| description | A cryptocurrency is a digital form of currency that is secured using an online ledger with cryptography. The first successful cryptocurrency was Bitcoin, which was launched in 2009 by an anonymous person under the pseudonym Satoshi Nakamoto. Similar to stocks, they can be bought and sold, and their prices can vary over time. Thus, being able to classify cryptocurrencies is key for a crypto investor to determine which crypto assets are worth investing in. This thesis will apply unsupervised learning to crypto whitepapers to cluster various cryptocurrencies. |
| first_indexed | 2024-09-23T16:41:26Z |
| format | Thesis |
| id | mit-1721.1/144527 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T16:41:26Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1445272022-08-30T03:03:03Z Unsupervised Crypto Clustering with NLP Zhang, Sammy Durand, Frédo Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science A cryptocurrency is a digital form of currency that is secured using an online ledger with cryptography. The first successful cryptocurrency was Bitcoin, which was launched in 2009 by an anonymous person under the pseudonym Satoshi Nakamoto. Similar to stocks, they can be bought and sold, and their prices can vary over time. Thus, being able to classify cryptocurrencies is key for a crypto investor to determine which crypto assets are worth investing in. This thesis will apply unsupervised learning to crypto whitepapers to cluster various cryptocurrencies. M.Eng. 2022-08-29T15:53:33Z 2022-08-29T15:53:33Z 2022-05 2022-05-27T16:19:34.359Z Thesis https://hdl.handle.net/1721.1/144527 In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Zhang, Sammy Unsupervised Crypto Clustering with NLP |
| title | Unsupervised Crypto Clustering with NLP |
| title_full | Unsupervised Crypto Clustering with NLP |
| title_fullStr | Unsupervised Crypto Clustering with NLP |
| title_full_unstemmed | Unsupervised Crypto Clustering with NLP |
| title_short | Unsupervised Crypto Clustering with NLP |
| title_sort | unsupervised crypto clustering with nlp |
| url | https://hdl.handle.net/1721.1/144527 |
| work_keys_str_mv | AT zhangsammy unsupervisedcryptoclusteringwithnlp |