Adaptive Streaming Content Recommendation Engine

Create a machine learning-powered recommendation algorithm using TensorFlow.js that dynamically generates personalized content suggestions for a streaming platform. Implement a hybrid recommendation system combining collaborative filtering, content-based filtering, and user behavior analysis, with explicit support for handling cold-start problems for new users and content. Design the algorithm to provide real-time recommendations with less than 50ms latency and include A/B testing infrastructure to continuously validate recommendation quality.