This project implements a Music Recommender System using Streamlit and Spotipy. It allows users to discover new music based on their favorite tracks.
- Song Recommendation: Recommends similar songs based on user input.
- Visual Representation: Displays album covers and Spotify links for recommended songs.
- Customization: Users can specify the number of recommendations they want to receive.
- Python
- Streamlit
- Spotipy (Python library for Spotify Web API)
- Pandas
- Scikit-learn (for TF-IDF vectorization and cosine similarity)
- NLTK (for natural language processing tasks)
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Clone the repository:
git clone https://github.com/your-username/music-recommender-system.git cd music-recommender-system
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Install dependencies:
pip install -r requirements.txt
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Run the Streamlit app:
streamlit run app.py
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Use the Music Recommender:
- Select or type in a song name.
- Specify the number of recommendations.
- Click on "Show Recommendation" to see the results.
- Thanks to Spotipy for the Python library to interact with the Spotify Web API.
- Inspired by the idea of recommending music based on user preferences.