This project was developed as part of the Predictive Analytics course, focusing on analyzing and interpreting medical stock data. The key objectives were to use statistical and machine learning techniques to derive actionable insights from historical stock prices in the medical sector.
- Data Preprocessing: Handling missing data, outliers, and data normalization.
- Predictive Models: Regression models like Linear Regression and Random Forest.
- Visualization: Graphs and dashboards for data insights.