Current music streaming platforms often fall short in delivering truly personalized recommendations, relying on algorithms that may not adequately capture individual preferences. This results in a less engaging and tailored music discovery experience, limiting the potential for users to explore new and exciting songs that align with their unique tastes.
To address this problem, our project aims to develop a web-based platform that utilizes an option-based interface, allowing users to indicate their musical preferences by creating a tracklist containing their personal favorites. The platform will not only recommend songs based on these preferences but also actively seek and incorporate user feedback, enhancing the overall user experience and providing a more tailored music recommendation service.
To run the React App in development mode, run npm i followed by npm start.
To run the server to start the Python script, run node server.js.
Utilsfolder contains the utility functions required for the ML algorithm.Datafolder contains the dataset used for preprocessing and searching similar songs.track_info.csvcontains the input tracks given by the user.ratings.jsoncontains individual ratings of each user.recom.jscontains the recommendations provided by the ML algorithm.