CSCI-4220 Music Recommendation App

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.

Table of Contents

• Features
• Installation
• Usage
• Dependencies
• License

Features

• 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

Installation

1. Clone this repository:

git clone https://github.com/brice-allen/summer.git

2. Create a virtual environment and activate it:

python -m venv venv
source venv/bin/activate  # For Windows: venv\Scripts\activate

3. Install the dependencies:

pip install -r requirements.txt

Usage

1. Activate the virtual environment:

source venv/bin/activate  # For Windows: venv\Scripts\activate

2. Run the Streamlit app:

streamlit run app.py

3. Open the provided URL in your web browser to start using the app.

Dependencies

- streamlit
- pandas
- scikit-learn
- plotly
- streamlit-components
- pillow

License

This project is licensed under the MIT License. See LICENSE for more information.