MortgageMate: Smart Home Choices for First-Time Buyers

Helping first-time home buyers make informed decisions by offering personalized housing options within their budget and providing detailed mortgage calculations, all through a user-friendly dashboard.

Comment

Inspiration

Buying a home is a significant milestone, but for first-time buyers, it can be daunting due to financial complexities. We wanted to create a solution that simplifies the decision-making process by offering easy access to available housing options and personalized mortgage details, empowering users to make informed choices.

What it does

The tool uses AI that allows first-time home buyers to input their budget and preferred location, providing a list of available houses that meet their criteria. Upon selecting a house, the tool calculates mortgage details based on the selected house price, and offers mortgage options for 5, 15, or 30 years with respective interest rates. The monthly payment and overall mortgage breakdown are presented in a clean, interactive dashboard.

How we built it

  • We used the (DMV) Washington D.C., Virginia, Maryland Housing Market 2024 dataset to train the model for house selection based on budget and city.
  • Python (with Pandas and Scikit-learn) was used for data preprocessing.
  • AI models such as Linear Regression and K means clustering were used for house matching and recommendation.
  • The mortgage calculator was built using simple financial formulas.
  • The interactive dashboard was developed using Gradio for clear visualization of housing and mortgage details.## Challenges we ran into

Accomplishments that we're proud of

  • Successfully built a tool that simplifies a complicated financial decision process for first-time home buyers.
  • Implemented a mortgage calculator that provides clear and accurate financial breakdowns.
  • Developed a clean, user-friendly dashboard that makes decision-making easier.

What we learned

-Working with nested JSON datasets, extracting relevant attributes, and cleaning the data for meaningful analysis.
-Building an interactive dashboard that balances functionality and simplicity for non-technical users.

What's next for First-Time Home Buyer Assist

  • Expanding the tool to cover more cities and housing markets across the U.S.
  • Enhancing the model to include more variables such as neighborhood amenities, school ratings, and proximity to transportation.
  • Adding more customizable financial options such as down payment percentages and varying interest rates.
Share this project:

Updates