🔹 Features ✅ Multi-Category Recommendations – Get tailored suggestions across music, podcasts, and audiobooks. ✅ Hybrid AI Model – Uses collaborative filtering, content-based filtering, and deep learning to enhance recommendations. ✅ Personalized Playlists – Auto-generate playlists based on mood, genre, and past listening behavior. ✅ Smart Podcast & Audiobook Chapters – Recommend specific chapters or timestamps of interest. ✅ Real-Time Adaptive Suggestions – Updates recommendations dynamically based on recent interactions. ✅ Cross-Domain Insights – Connects user interests across music, podcasts, and audiobooks. ✅ Explainable AI – Shows why a particular recommendation was made.
🔹 Machine Learning: Collaborative Filtering, Content-Based, Deep Learning (Transformers, Embeddings) 🔹 Backend: Python (FastAPI/Flask) 🔹 UI: Streamlit 🔹 Database: PostgreSQL, Redis (for caching), Neo4j (for graph-based recommendations) 🔹 Deployment: Docker, AWS/GCP
🚀 Social features – Follow users, share playlists 🚀 Voice search & assistant integration 🚀 Multi-language support