🔍 I explored the Boston Housing Dataset and cleaned the data by handling missing values and outliers using winsorization.
🧪 Next, I performed feature engineering and selection to identify the most significant variables that affect housing prices.
💻 I then implemented the linear regression model and evaluated its performance using various metrics such as R-squared, mean squared error, and root mean squared error.
📈 Finally, I made predictions on new data and visualized the results using Matplotlib.
🤖 This project has helped me sharpen my skills in data cleaning, feature selection, linear regression modeling, and data visualization