Inspiration

In 2014, over 40 veterans passed away while waiting for care at Veterans Health Administration. The fact that some of the bravest Americans are beating beaten by waiting times is not something we should be proud of. It should be in all of our best interests that veterans come home to the best care this country has to offer.

What it does

There are two parts to our project. The first is a website that provides relevant information for military members and their families. By compiling a list of relevant APIs and formatting it for a user friendly experience, we have made the struggle of finding the best care facility a little more manageable.

For the long term, we used used Fiscal Note's API to research voting records of US representatives to shed light on America's stance on veterans. While every bit helps, we should not be satisfied with a slightly lesser burden for searching for care. As such, we used machine learning to analyze the text of recent bills. By providing a better understanding of our government's policies, we hope to encourage more people to vote and implement the changes they wish to see themselves.

How I built it

The website was built using HTML, CSS, Django, Mongodb, Javascript, Jquery and Python. In order to manipulate the data as well as possible, we switched languages fairly frequently. The APIs used came from the Veteran's Affair's website.

The research into the bills was done exclusively in Python. We utilized gensim and word2vec in order numerically analyze the language of the bills.

What's next for Welcome HomePage

The research was a late addition to our project. As a result, we could not do a second layer of analysis (We used clustering to analyze the data, but I would have also liked to have used vector averages in order to see consistencies within the bill itself).

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