This repository contains the code for a music recommender system for Radio Javan. The system is designed to suggest songs based on user preferences and listening history. It utilizes TF-IDF for text analysis and incorporates various music features such as danceability, energy, and more.
- Python 3.6 or higher
- Jupyter Notebook
- Clone the repository
git clone https://github.com/parvvaresh/Music-recommender-system.git
- Navigate to the project directory
cd Music-recommender-system
- Create and activate a virtual environment
python3 -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate`
- Install the required packages
pip install -r requirements.txt
- Start Jupyter Notebook
jupyter notebook
- Open the
.ipynb
file in the Jupyter interface to run the code cells interactively.
- Ensure your virtual environment is activated
- Run the Python script
python script_name.py
Contributions are welcome! Please follow these steps to contribute:
- Fork the repository
- Create a new branch (
git checkout -b feature/YourFeature
) - Commit your changes (
git commit -m 'Add some feature'
) - Push to the branch (
git push origin feature/YourFeature
) - Create a new Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Any libraries, datasets, or tutorials that were particularly helpful.
- Any contributors or collaborators.
- TF-IDF for Text Analysis: Utilizes Term Frequency-Inverse Document Frequency (TF-IDF) to analyze textual data.
- Music Features: Incorporates various music features such as danceability, energy, and more to enhance recommendations.