House Price Prediction

House Price Prediction

Developed a Machine Learning regression system for estimating residential property prices based on property characteristics such as area, number of bedrooms and bathrooms, house age, parking spaces, distance to the city center, and location.

The project includes data preprocessing, feature engineering, categorical encoding, feature scaling, and comparison between Linear Regression and Random Forest Regression.

Model performance was evaluated using R², MAE, and RMSE to measure prediction quality.