Freehold Price Predictor
A real estate price prediction platform for Bangalore home prices using Machine Learning.
System Architecture Flow
Data Ingestion
Raw Bangalore property data collected and cleaned using Pandas.
Model Training
Linear Regression model trained and optimized using Scikit-learn.
Flask API
Trained model exported and served via a Python Flask server.
React Frontend
User inputs details and receives prediction via API call.
Deployment
System hosted on AWS EC2 with Nginx as a reverse proxy.
What we have used
Python (NumPy, Pandas, Matplotlib) for data cleaning and exploration.
Scikit-learn for building the Linear Regression model.
GridSearchCV for hyperparameter tuning to find the best model configuration.
Flask (Python) as the backend server to serve model predictions.
React for the frontend user interface.
Nginx and AWS EC2 for infrastructure and deployment.
Uses & Applications
Allows property buyers and sellers in Bangalore to estimate market value based on area, BHK, and location.
Provides a clean UI for inputting property details and receiving instant predictions.
Demonstrates an end-to-end ML pipeline from raw data to a production web app.
Future Roadmap
Expanding the model to cover other major Indian cities.
Integrating more advanced algorithms like Random Forest or Gradient Boosting for higher accuracy.
Adding real-time market trend visualizations and neighborhood safety scores.