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This project uses machine learning to recommend songs on Spotify based on the audio features of a user-selected song. The program extracts relevant features, calculates distances between tracks, and sorts recommendations in ascending order. The final output is a CSV file containing recommended songs with their name, artists, and Spotify URL.

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Song-Recommendation-System-using-Spotify-Audio-Features

The project is designed to generate a playlist of recommended songs based on a given track using machine learning techniques.

pip install spotipy
pip install pandas
pip install scikit-learn

After installing the libraries, you need to create a vars.py file with your Spotify API credentials. In this file, create two variables stored_client_id and stored_client_secret with your credentials, like this:

stored_client_id = 'your_client_id_here'
stored_client_secret = 'your_client_secret_here'

You can obtain your credentials by creating a Spotify developer account and creating a new app.

Next, download the model from here and place it in the root directory of the project.

Run the script.py file with py script.py command, and then enter a URL of the Spotify song you want recommendations for.

Contributing

Please feel free to fork this repository and contribute by submitting a pull request to enhance the functionality.

Presentation

Here you can find an overview of this project.

License

This project is licensed under the MIT License.

About

This project uses machine learning to recommend songs on Spotify based on the audio features of a user-selected song. The program extracts relevant features, calculates distances between tracks, and sorts recommendations in ascending order. The final output is a CSV file containing recommended songs with their name, artists, and Spotify URL.

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