Please use this identifier to cite or link to this item: 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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