Variefy is an app that creates Spotify playlists of fresh, unfamiliar music tailored to a user's taste. It uses K-Means clustering to categorize a user's top 50 songs into four representative types. Users can then choose a category to generate a playlist with personalized recommendations.

You might be wondering? What's the problem my team and I tried to solve?

Variefy aims to address the problem of discovering unfamiliar or fresh music that aligns with a user's current music taste. By analyzing the user's top songs and clustering them into distinct categories, the app provides recommendations that are similar to the user's preferences but potentially introducing new and diverse tracks.

Tech Stack:

  • Spotify API

  • Vue.js

  • ExpressJS

  • Node.js

  • TensorFlow / Scikit.js

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