Music Recommendation System using Python
Mr. Chirag Desai, Shubham Bhadra, M. Parekh · International Journal for Research in Applied Science and Engineering Technology · 2023
Abstract: In contrast to the past, the availability of digital music has increased thanks to online music streaming services that can be accessed from mobile phones. It becomes tedious to sort through all of the songs and results in information overload. Many people consider music to be an integral part of their lives and place great value on it. When a person is joyful, depressed, or emotional, he prefers to listen to music to unwind his mind. Users frequently use search engines to find songs of interest to them, but as technology has advanced, other approaches to searching have been adopted. As a result, creating a music recommendation system that can browse song albums automatically and suggest appropriate songs to users is quite advantageous. Utilising such system based on the user’s mood, it can anticipate and then present the appropriate songs to its users. Our work is unique in that the developed recommender system is based on the user’s mood. There are two known methods for creating content-based music recommendation systems. The first methodology, which makes use of a powerful classification algorithm, is quite popular, while the second one uses deep learning algorithms to augment the performance of the recommender system.