Introduction to the Music Recommendation System
Explore how to create a music recommendation system by extracting song attributes and audio features to generate embeddings. Learn to store and query these embeddings in a vector database to recommend similar tracks based on user preferences and song characteristics.
A music recommendation system is a type of recommendation system designed to suggest music tracks, albums, or artists to users based on various factors such as user preferences, listening history, or the characteristics of the music itself.
We will design a music recommendation system that suggests tracks based on the characteristics of the music itself, such as the attributes of the songs and the audio features. Attributes include genre, danceability, energy, loudness, speechiness, acousticness, instrumentalness, liveness, ...