Dynamic Content Recommendation ML Pipeline

Architect a machine learning recommendation engine using TensorFlow.js that dynamically personalizes streaming content suggestions. Implement a hybrid recommendation system combining collaborative filtering and content-based approaches, with client-side inference to reduce server load. Design the system to handle privacy-preserving feature extraction, support A/B testing of recommendation algorithms, and provide transparent explainability for why specific content is recommended.