Real Estate Price Prediction

    Developed regression models to predict real estate prices and visualized key factors in an interactive dashboard.

    Muhammad Zeeshan

    Technologies Used

    Python
    scikit-learn
    XGBoost
    Pandas
    Plotly
    Streamlit

    Key Features

    1

    Multiple regression models (Linear, Ridge, XGBoost)

    2

    Feature importance visualization

    3

    Interactive price prediction interface

    4

    Neighborhood-based analysis

    5

    Market trend visualization

    Implementation

    Built an end-to-end ML pipeline for real estate price prediction using ensemble methods. Performed feature engineering on property characteristics, location data, and market indicators. Created an interactive dashboard for predictions.

    Results & Impact

    Achieved R² score of 0.89 on test data. Successfully identified top 5 price-influencing factors: location, square footage, number of bedrooms, age, and proximity to amenities.