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https://hdl.handle.net/10356/165811
Title: | Venture capital horizon scanning | Authors: | Singapuri, Bhargav Piyushkumar | Keywords: | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence | Issue Date: | 2023 | Publisher: | Nanyang Technological University | Source: | Singapuri, B. P. (2023). Venture capital horizon scanning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165811 | Project: | SCSE22-0633 | Abstract: | Private 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%. | URI: | https://hdl.handle.net/10356/165811 | Schools: | School of Computer Science and Engineering | Organisations: | Vertex Venture Management Private Limited | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
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Bhargav_FYP.pdf Restricted Access | 2.63 MB | Adobe PDF | View/Open |
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