Music Recommendation System Using Real Time Parameters

The use of music as a means of calming, energizing, and motivating oneself is widely popular. With the help of modern technology, the goal is to recommend suitable music for various situations. This project aims to achieve this by utilizing real-time data such as time, location, weather, facial expressions, artists, and audio attributes to accurately determine the user's emotional state. Machine learning algorithms like CNN and DNN will be used to create a model that can classify song samples into different genres and Spotify API and LastFM API are connected to the user's database to recommend music based on the individual's parameters. The ultimate objective is to provide personalized music recommendations to users.