Querying the Database to Generate Recommendations
Explore how to query vector databases to develop a music recommendation system. Learn to use metadata embeddings, audio embeddings, and combined results to find and rank similar songs effectively, enhancing your understanding of recommendation techniques.
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 ...