abhit20/ML-Startup-Success
ICAIF 2021 Paper "A Machine Learning Approach to Detect Early Signs of Startup Success"
This project helps investors, venture capitalists, or government grant agencies assess the future success of early-stage startups. By inputting details about a company's SBIR/STTR award and Crunchbase profile, it predicts the likelihood of an IPO or M&A event. The output is a prediction of startup success, helping those who fund or support small businesses make more informed decisions.
No commits in the last 6 months.
Use this if you need to evaluate the potential viability of small ventures and identify factors contributing to their future success.
Not ideal if you are looking for real-time market predictions or a tool to manage existing investment portfolios.
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18
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5
Language
Jupyter Notebook
License
MIT
Category
Last pushed
May 23, 2022
Commits (30d)
0
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