Querying the Database to Generate Recommendations
Explore how to query vector databases to build a music recommendation system. Learn to generate recommendations using metadata embeddings, audio embeddings, or a combination of both. Understand how to extract, combine, and rank similar songs to deliver relevant and personalized music suggestions.
We will use a song from the dataset as the one the user is currently listening to and, based on this song, recommend the top five similar songs.
There are three ways we can find similar songs: using metadata embeddings, audio embeddings, or both.
Recommendations based on metadata embeddings
In the following code, we get the embedding for the song the user is currently listening ...