Introduction to the Music Recommendation System

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, valence, and tempo.

Dataset

We’ll take a smaller portion of the Mood-Based Music Recommendation System Datasethttps://www.kaggle.com/datasets/maulipatel18/mood-based-music-recommendation-system-dataset from Kaggle. There are 8 genres, and we have picked 10 songs from each, so our dataset consists of 80 songs.

In our dataset, we have a folder containing the audio files and a CSV file containing the songs’ metadata.