Linear Regression model to forecast stock prices from historical data (open, high, low, volume, 5/365-day moving averages). Trained up to 2013, tested beyond. Steps: preprocessing, feature engineering, training, MAE/MAPE evaluation. Interactive Gradio UI. Correlation studies and engineered features (5-day std and mean close) improved accuracy.