This is a music recommendation app built using Streamlit, Python, and the Spotify API. The app utilizes the K-Nearest Neighbors algorithm to provide personalized music recommendations based on user preferences.
- Interactive sliders for selecting music preferences
- Recommendations based on genre, release year, and various audio features
- Visualizations of song features using Plotly
- Pagination for easy navigation through recommendations
- Responsive design
- Clone this repository:
git clone https://github.com/brice-allen/summer.git- Create a virtual environment and activate it:
python -m venv venv
source venv/bin/activate # For Windows: venv\Scripts\activate- Install the dependencies:
pip install -r requirements.txt- Activate the virtual environment:
source venv/bin/activate # For Windows: venv\Scripts\activate- Run the Streamlit app:
streamlit run app.py- Open the provided URL in your web browser to start using the app.
- streamlit
- pandas
- scikit-learn
- plotly
- streamlit-components
- pillow
This project is licensed under the MIT License. See LICENSE for more information.