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Enhancing venture capital investment strategies through automated web data collection and analysis
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| 1015.32 KB | Adobe PDF |
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Orientador(es)
Resumo(s)
“Identifying investment opportunities is crucial for every venture capital fund, yet this process
is often labor-intensive, time-consuming, and profoundly relies on the gut feeling of
investment professionals. With new companies being discovered every day and intensified
competition among funds, it has become increasingly challenging to recognize the most
attractive prospects quickly. Machine learning-based decision support brings objectivity to
this process, reducing the need for intuition. By applying supervised machine learning
techniques to rate deals identified through web crawling and proprietary fund data, I found
that random forest models perform exceptionally well, significantly cutting down the time
spent on deal sourcing.
Descrição
Palavras-chave
Venture capital Startups Web scraping Web crawling Artificial intelligence Machine learning