We wanted mortgage applicants to be more confident about buying homes. Buying a home is a one-time decision and a very big investment for many.
What it does
Buying a home is a very big decision in life. When people like us go to a bank for mortgage applications, we want to be sure that the house we are buying will be safe to live, will increase in value over the years. Our app uses ML to predict the prices for 5 years and scrapes the database for past crimes that happened in the vicinity. Then, it provides the user with the best mortgage buying option. To aid the user, our app sends SMS to the user's phone, through which the user can see their prospective home in Google Street View.
How We built it
We built it, with a team of 3 people, Abiral, Ashish and Abubakr. We used ML, SQL and database scraping.
Challenges We ran into
We, as usual, since we are not pro with Python, had problems with Python data types. Making Python coexist with maps API was really painful.
Accomplishments that We're proud of
We are proud of the ideas that we generated by brainstorming. We revised ML algorithms since it had been a lot since we had last used it.
What We learned
I learned about google maps API, integrating python to google cloud, how to use APIs, and in hackathon workshops, I learned about vision and AR.
What's next for VR Based Customer Mortgage App
Using much more features to predict, rather than just a few we used in hackathon due to time limitation.