Great choice for a final project! Here's a structured approach for your music
playlist recommendation system:
1. Data Collection & Preprocessing
-
Use the Million Song Dataset or Spotify's API for user listening history
- Create a user-item interaction matrix
- Handle cold start problems with content-based fallbacks
2. Model Architecture
- Start with matrix factorization (SVD) as baseline
- Implement neural collaborative filtering for comparison
- Consider hybrid approach combining collaborative + content features
3. Evaluation
- Use NDCG@K and MAP for ranking quality
- A/B test against random and popularity baselines
- Cross-validation with temporal splits
Shall I help you set up the project structure and data pipeline first?