What it does
We built TraveLink, a travel management web app that recommends hotel stays and musical events based on the interests and similarities of different travelers in such a way that matching travelers end up in the same locations in order to connect and have an improved traveling experience.
More specifically, TraveLink offers three ways to connect travelers:
- Based on basic travel interests and networking preferences.
- Based on an analysis of their own Twitter feed to detect interests.
- Based on favorite music genres via the Spotify web API.
How we built it
We built the entire project using Python. We used a K-means clustering machine-learning model to find travelers with matching interests.
Challenges we ran into
Working with front-end development was challenging because none of us were front-end developers. Also challenging was dealing with APIs such as the Spotify web API.
Accomplishments that we're proud of
We are proud of having produced a relatively simple but functional product.
What we learned
We learned that full-stack development is challenging.
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