Personalized Content Recommendation Machine Learning Pipeline

Create an advanced recommendation engine using TensorFlow and scikit-learn that generates personalized content suggestions for a streaming platform. Develop a hybrid collaborative filtering and content-based recommendation system that can process user interaction data, content metadata, and viewing patterns. Implement feature engineering techniques to extract complex user preference signals, and design a model that can be retrained incrementally without full dataset reprocessing. Include A/B testing infrastructure to measure recommendation accuracy and user engagement.