- Developed a house cost predictor that accurately estimates the total cost of homeownership, encompassing property taxes, insurance, and maintenance, thereby empowering buyers to make informed financial decisions with up to ~8% improved accuracy based on house price.
- Conducted extensive exploratory data analysis and feature engineering, leveraging scaling and hyperparameter tuning techniques. Achieved a ~25% reduction in prediction error using Random Forest Regression and XGBoost, and successfully deployed the model on Streamlit Cloud.
If you find it useful, please consider starring the repository on GitHub to support my work: GitHub - jash0803/Property_Acquisition_Cost_Predictor_Steamlit_Cloud: Deployed using Streamlit Cloud
Also, if you want to make an app on Streamlit, I am interested in doing freelancing projects or working part-time to build apps. Thanks:)