Music Recommendation System using Spotify API

Overview: This repository contains code for a music recommendation system that utilizes the Spotify API to extract music data and provide personalized recommendations based on user input. The system employs a hybrid approach, combining content-based filtering and popularity-based scoring to generate relevant recommendations.

Live Demo

Key Features:

1. Accessing and Tokenization: The system authenticates with the Spotify API using client credentials and obtains an access token for data extraction.

2. Spotify Music Data Extraction: It fetches music data from a specified playlist, including track information such as name, artists, album, release date, and audio features like danceability, energy, and tempo.

3. Data Preprocessing: The extracted data is processed and normalized using techniques like Min-Max scaling to prepare it for recommendation algorithms.

4. Content-Based Recommendations: Based on the input song provided by the user, the system calculates similarity scores using cosine similarity on audio features and suggests similar songs from the playlist.

5. Hybrid Recommendation System: It integrates content-based recommendations with popularity-based scoring, considering factors like release date and track popularity to provide more personalized and diverse recommendations.

Repository Structure:

• music_recommendation.ipynb: Jupyter Notebook containing the code for the music recommendation system.
• README.md: Markdown file providing an overview of the project, setup instructions, and usage guidelines.
• requirements.txt: Text file listing the required Python packages and their versions for running the code.
• LICENSE: License file specifying the terms of use for the project.

Usage:

1. Clone the repository to your local machine.
2. Install the required dependencies listed in requirements.txt.
3. Obtain your Spotify API client ID and client secret and replace them in the code.
4. Run the music_recommendation.ipynb notebook to execute the recommendation system.
5. Follow the instructions within the notebook to input a song and receive personalized recommendations.

Contributing:

Contributions to the project are welcome! If you have any suggestions, improvements, or bug fixes, please open an issue or submit a pull request following the project's contribution guidelines.

License:

This project is licensed under the MIT License.

Disclaimer:

This project is for educational and demonstration purposes only. It does not store any user data and solely relies on the Spotify API for music recommendations.

Acknowledgements:

• This project utilizes the Spotipy library for interacting with the Spotify API.
• Special thanks to Spotify for providing access to their API for developers to build innovative applications.