Interactive Content Recommendation Neural Network

Build a TensorFlow-powered recommendation engine for a streaming platform that predicts user content preferences with 85%+ accuracy. Develop a hybrid collaborative filtering and content-based recommendation system that incorporates user viewing history, genre preferences, and temporal watching patterns. Include feature engineering for metadata extraction, implement gradient boosting for prediction optimization, and create a modular recommendation pipeline that can be easily retrained with new datasets.