A simple machine learning project that recommends music tracks based on user preferences using TensorFlow and the Spotify API.
This recommendation system ingests user listening history from Spotify and processes the data using TensorFlow models to generate track recommendations.
- Fetch user listening history with the Spotify API.
- Process and analyze data to identify user preferences.
- Use TensorFlow deep learning models for recommendation predictions.
- Generate a playlist with recommended tracks.
- Python 3.x
- Spotify account
- Spotify Developer API credentials (Client ID & Client Secret)
- Clone the Repository:
git clone https://github.com/your_username/music-recommender.git cd music-recommender