Navigating the realm of innovative business ideas is a daunting task, with the elusive nature of groundbreaking concepts. This challenge is vividly illustrated on the popular platform, Shark Tank, where aspiring entrepreneurs present their ventures to a panel of investors, known as Sharks. The dynamic involves negotiating a deal, often involving relinquishing a percentage of their business in exchange for financial backing and the invaluable mentorship, connections, and expertise of the Sharks. The highstakes nature of these negotiations compels the Sharks to meticulously scrutinize business profits, records, and performance, aiming to validate the purported valuation of the business.
Recognizing the intricacies involved in this venture underscores the potential value of a predictive model capable of accurately forecasting whether a business can secure a deal. Moreover, the insights gleaned from previous pitches can empower entrepreneurs, offering them a strategic advantage in positioning themselves for success while optimizing their use of time and resources.This project aims to develop a classification model to predict business success on the platform, while also conducting exploratory data analysis and clustering to extract actionable insights from past pitches, thereby providing a valuable resource for aspiring entrepreneurs.