What it does

Our application accepts a variety of data from a potential customer and uses it to recommend the quality of health insurance (Bronze, Silver, Gold, and Platinum) that the customer should get. Our application will also show them how they compare to others and will give them prices for each quality of health insurance.

How we built it

The front end was built using HTML, CSS, JavaScript, and various javascript libraries. The back end was built using machine learning (Google's Cloud ML and TensorFlow) to develop an informed decision and we used Vitech's database of participants to train and verify our machine learning model. We used Flask to communicate data between the front end and the back end.

Challenges we ran into

Everyone in our team wanted to learn and use new programming languages and tools to make this project. We spent 8 hours in the beginning of the hackathon thinking of ideas and learning how to utilize the various APIs we planned on using and the new languages that we planned on adding to our library.

Accomplishments that we're proud of

We are proud of effectively working together as a team to build something. We split the roles and when the time came to combine the different sections of code, our constant communication made it a seamless process. We were excited to learn machine learning and to expose ourselves to all the other APIs and languages that we didn't know about until this hackathon.

What we learned

Aside from learning machine learning and other programming tools, we also learned that we worked well as a team. Despite everyone's varied experience in programming, we were able to harmonize to create something nice.

What's next for Get a Quote

Next time, we will be working on auto insurance.

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