Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/165811
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dc.contributor.authorSingapuri, Bhargav Piyushkumaren_US
dc.date.accessioned2023-04-12T08:35:13Z-
dc.date.available2023-04-12T08:35:13Z-
dc.date.issued2023-
dc.identifier.citationSingapuri, B. P. (2023). Venture capital horizon scanning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165811en_US
dc.identifier.urihttps://hdl.handle.net/10356/165811-
dc.description.abstractPrivate Equity firms need to rely on larger and more diverse sources of data in order to make risk-aware investment decisions. Persons involved with making the investment decisions need tools that allow them to gain insight from such vast quantities of data. One part of that whole system is trying to understand what industry the company they are seeking to invest in are from and their specialities and characteristics. This Project fine tunes a Large Language Model to classify companies into their industries based on the description of the company. It is trained on data acquired from LinkedIn of over 64 million companies. It achieves a F1 score of 0.7101 and a Top-5 Accuracy of 88.83%.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationSCSE22-0633en_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleVenture capital horizon scanningen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLee Bu Sung, Francisen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Science in Data Science and Artificial Intelligenceen_US
dc.contributor.organizationVertex Venture Management Private Limiteden_US
dc.contributor.supervisoremailEBSLEE@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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