Is the Company going to be successful?

Empowering data-driven decision-making in venture capital with the use of predictive modeling techniques for forecasting startup success.

In this project, I've taken a practical step towards enhancing venture capital decisions by applying predictive analytics to startup evaluation. By analyzing a Kaggle dataset with R, I've developed models that consider various factors like funding and milestones, aiming to identify contributors to a startup's success. I've kept my approach realistic, acknowledging the volatility of the startup world and the need for continuous adaptation and improvement. My findings, which underscore the importance of early investments and networking, serve as a solid foundation for further nuanced exploration into the predictive potential of venture success.