The project cleans and prepares datasets of historical stock prices and fundamentals using pandas, then applies scikit-learn classifiers to discover relationships between financial metrics (PE ratio, debt/equity, etc.) and subsequent annual price changes. It includes a simple backtesting framework and generates predictions on current data, serving as both a learning guide and starting point for quantitative trading strategies.