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Inspiration
We believed there is a better more entertaining way to go about making playlists and discovering music! Utilizing the k-nearest-neighbors model as inspiration for our nodes (that represent music), we created a recommendation model that delivers what we believe Spotify couldnt!
What it does
Our program delivers an immersive, personalized listening experience for music lovers worldwide. By selecting a preferred track from recurring nodes through a vast ocean of songs, users unlock a smart system that curates a playlist tailored to their unique tastes. Using the essence of each song, our technology seamlessly connects them with similar tracks, creating a dynamic soundtrack designed just for them.
How we built it
Utilizing Python and NodeJS primarily
Challenges we ran into
APIs not working and authorization issues. Also, this was a huge learning process for us. We enjoyed learning new concepts and skills along the way for the future.
Accomplishments that we're proud of
Learning new skills in such a short time! We stayed up both nights and tried out hardest :)
What we learned
Have a more organized structure for more organized deployment
What's next for Weaver
Incorporating databases, creating better user experience, OAuth, etc.
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