Formula 1 Race Outcomes – Analysis and Predictions

Collected and analyzed data of Formula 1 races to develop a predictive model for forecasting future race outcomes using Web Scraping, Data Mining and Machine Learning techniques like Regression, Clustering and Gradient Descent.

The project is built upon the idea of using data mining to extract insights and predictions from complex and large datasets. We applied this idea to the domain of Formula 1 racing, leveraging the vast amount of historical data available to develop a predictive model that can forecast the outcomes of future races with a high degree of accuracy. By combining cutting-edge data mining techniques with domain-specific expertise, we hope to contribute to the ongoing development and evolution of this exciting and dynamic sport.