Gurgaon Real Estate App

Welcome to the Gurgaon Real Estate App, an innovative Streamlit application designed to revolutionize the way users interact with real estate data in Gurgaon, India. This application harnesses the power of machine learning and data analytics to provide insightful and personalized real estate experiences.

Features

• Price Prediction Module: Utilizes advanced machine learning algorithms to predict property prices based on various attributes like the number of bathrooms, rooms, amenities, etc.
• Recommender System: Guides users to top nearby properties based on personalized criteria, enhancing user engagement and decision-making.
• Analytical Module: Offers deep dive analyses into property rate trends, area pricing, and comparative market analysis, empowering users with comprehensive market insights.

Technologies Used

• Streamlit: For creating a user-friendly web application.
• MLFlow: To track model performance and metrics efficiently.
• Docker: Ensures consistent deployment and scalability by containerizing the application.
• Amazon EC2: Automated deployment to EC2 servers facilitates robust CI/CD pipelines, ensuring efficient delivery and high availability.
• DVC: For version control, ensuring that data and model changes are systematically managed.
• Amazon S3: Hosts data files, providing reliable and scalable storage solutions.

Getting Started

To get a local copy up and running, follow these simple steps:

1. Clone the repository:

git clone https://github.com/SiddhantH1512/housepriceproject.git

1. Navigate to project directory:

cd housepriceproject

2. Install required dependencies:

pip install -r requirements.txt

3. Run the streamlit app:

streamlit run app.py

Data Source

The data used in this project was obtained through web scraping from 99acres.com. This data forms the backbone of our predictive

Author

SiddhantH1512 - Feel free to connect with me on GitHub for any questions, suggestions, or collaboration related to this project.

GitHub: SiddhantH1512

Contact

If you have any questions, feedback, or would like to get involved with the project, please don't hesitate to reach out. You can contact me directly through GitHub or by raising an issue on the project repository.

• GitHub Issue Tracker: Report Issues
• GitHub Profile: SiddhantH1512