🏡 Bengaluru Property Price Prediction App

An interactive Streamlit app that predicts property prices in Bengaluru (Bangalore), India, based on various inputs like location, square footage, BHK (bedrooms), and bathrooms.

🔍 Features

• User-friendly web interface built with Streamlit.
• Real-time price predictions using a trained machine learning model (Random Forest / Linear Regression).
• Clean data pipeline with included dataset and preprocessing handled in the notebook (Bengaluru_House_Price_Prediction.ipynb).
• Full deployment-ready code (including app.py, requirements.txt, model pickle, and metadata files).

🚀 Live Demo

Check out the live version here:
benglore-property-price-predict-app.streamlit.app

📁 Repository Structure

├── app.py # Streamlit app entry point ├── Bengaluru_House_Price_Prediction.ipynb # Exploration, modeling, feature work ├── bengaluru_house_prices.csv # Raw dataset ├── benglore_home_prices_model.pickle # Trained model ├── column.json # Metadata (feature names, locations, etc.) ├── requirements.txt # Python dependencies └── House.jpeg # UI image or illustration (optional)

🧩 Technologies Used

• Python
• Streamlit – for the front-end web app
• scikit-learn – for model training
• pandas & NumPy – for data processing
• Pickle – for model serialization