Dynamic Content Recommendation Engine for Streaming Platforms

Create a sophisticated recommendation algorithm using pandas and scikit-learn that generates personalized content suggestions for a streaming service. Develop a hybrid recommendation system combining collaborative filtering, content-based filtering, and user behavior analysis. Implement feature engineering techniques to extract meaningful user interaction patterns, with a minimum prediction accuracy of 85%. The system should handle complex user profiles across multiple content types (movies, games, music) and provide real-time recommendation updates.