mohammedt2059/nigeria-house-price-predictor

Machine learning project predicting house prices using GradientBoosting # 🇳🇬 Nigeria House Price Predictor A machine learning web application that predicts Nigerian house prices using property details such as location, number of rooms, and property type. ## Project Overview This project uses machine learning regression models to estimate house prices based on historical Nigerian real estate data. ## Features - Data cleaning and preprocessing - Exploratory Data Analysis - Feature engineering - Machine learning model comparison - Hyperparameter tuning - Streamlit deployment ## Models Tested - Linear Regression - Random Forest Regressor - Gradient Boosting Regressor ## Final Model Gradient Boosting Regressor Performance: - R² Score: 0.396 - MAE: ₦83 million - RMSE: ₦284 million ## Features Used - Bedrooms - Bathrooms - Toilets - Parking spaces - Property type - Town - State - Total rooms - Luxury property indicator - Location frequency features ## Deployment The application was built using Streamlit. Run locally: ```bash pip install -r requirements.txt streamlit run app.py