Housing Affordability Model

I built this project to make housing-price analysis more accessible and actionable. Instead of just creating a model, I wanted to turn the output into something people could actually use for decision-making.

what I did

1. 01AI cleaned and modeled a 20,000+ record housing dataset using multiple linear regression.
2. 02AI identified key price drivers such as size, quality, and build year, with model performance around R² ≈ 0.75.
3. 03AI built a Streamlit tool that translates model outputs into price prediction, feasibility analysis, cost breakdowns, and optimization scenarios.
4. 04AThe project pushed me to think beyond analysis and toward usability and applied value.

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