With fairly little experience in the Data Science/Machine learning space, I wanted to dive right in and tackle one of the data science problems that was presented at the hackathon.
What it does
It uses multiple linear regression to predict insurance quotes for each of the four insurance types that the insurance company, Intellisurance, would give to a person given data on the person such as income, preexisting conditions, Tobacco usage, marital status, etc. It then uses those predicted quotes to suggest to the user which plan they should get.
How I built it
Python for data science backend. HTML, CSS, and JS for frontend.
Challenges I ran into
I don't machine learning to begin with and apparently combining multiple categorical and continuous data for your features for a machine learning model does not lend itself to being easy.
What's next for HealthMe
Better algorithm and more graphs.