CHERYLDATA/house-price-prediction-kenya

# House Price Prediction (Kenya) ## Overview This project is a machine learning model that predicts house prices in Kenya using features such as location, number of bedrooms, bathrooms, and amenities. ## Technologies Used - Python - Pandas - NumPy - Scikit-learn - Matplotlib / Seaborn ## Project Workflow - Data collection and cleaning - - Handling missing values - - Feature engineering (amenities, location) - Model training using: - Linear Regression - Random Forest - - Model evaluation using RMSE and R² - ## Results The Random Forest model performed better than Linear Regression, showing improved accuracy in predicting house prices. ## How to Run the Project 1. Clone the repository: ```bash git clone github.com