Inspiration

We were interested in ViTech’s challenge and their API as it dealt with machine learning. It didn’t seem impossible to work with even though we aren’t highly experienced programmers, but the work required with this api was complex enough to pose a large challenge. ViTech’s API was not like any other we saw, it was more of a databank for big data. This was particularly interesting as we all wanted to make a large impact which would be possible when working around big data.

What it does

The project was designed to be a website that a prospective insurance purchaser could use. It should have included graphs and diagrams that compared different insurance factors. It also would have included machine learning to help users predict how much their insurance quote would be based off of 1.4M people’s insurance data. The project was designed to be a website that a prospective insurance purchaser could use. It includes graphs and diagrams that compare different insurance factors. It also includes machine learning to help users predict how much their insurance quote will be based off of 1.4M people’s insurance data.

How we built it

Python, JavaScript, and JQuery would have been used for the backend, while HTML and CSS would have been used for the front end.

Challenges we ran into

We ran into a couple unforeseen challenges while attempting to build our project. We quickly learned that JavaScript is very challenging. It has a lot of functionality with libraries and frameworks, and can get very confusing when attempting to implement confusing algorithms, databases, and libraries. Also, time management was a big challenge.

Accomplishments that we're proud of

It was impressive how much we coded in such a short time span. I was very lucky to have a talented group but they knew how to implement and teach me very well. Pranav was able to create a fantastic front-end program. Dipinjit was able to carry a large bulk of the back-end program and it was definitely difficult. Kajoban did the best with being versatile. He worked on both front and back-end programs and had only learned the languages at the same time I had learned them. Jefin was able to use logic and suggest logic for the programs and worked as an overall helping hand.

What's next for yTek

Although we weren't able to finish the project that we originally set out to complete. we do have other plans for this project. We are most likely going to shift focus from this API and try to incorporate another API in order to further expand our skills on machine learning.

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