Venture capital horizon scanning
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 t...
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Nanyang Technological University
2023
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sg-ntu-dr.10356-1658112023-04-14T15:37:32Z Venture capital horizon scanning Singapuri, Bhargav Piyushkumar Lee Bu Sung, Francis School of Computer Science and Engineering Vertex Venture Management Private Limited EBSLEE@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence 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%. Bachelor of Science in Data Science and Artificial Intelligence 2023-04-12T08:35:13Z 2023-04-12T08:35:13Z 2023 Final Year Project (FYP) Singapuri, B. P. (2023). Venture capital horizon scanning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165811 https://hdl.handle.net/10356/165811 en SCSE22-0633 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Singapuri, Bhargav Piyushkumar Venture capital horizon scanning |
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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%. |
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Lee Bu Sung, Francis |
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Lee Bu Sung, Francis Singapuri, Bhargav Piyushkumar |
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Final Year Project |
author |
Singapuri, Bhargav Piyushkumar |
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Singapuri, Bhargav Piyushkumar |
title |
Venture capital horizon scanning |
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Venture capital horizon scanning |
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Venture capital horizon scanning |
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Venture capital horizon scanning |
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Venture capital horizon scanning |
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venture capital horizon scanning |
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Nanyang Technological University |
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2023 |
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https://hdl.handle.net/10356/165811 |
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