Re-Ranking, Multi-Task Learning & Generative RecSys

Ranking is not just about accurately scoring candidates. Production recommendation systems must balance competing engagement goals, enforce business constraints, and leverage generative AI to deliver relevant, fair, and diverse results. This course teaches you to fine-tune the final mile using multi-task architectures, post-processing re-ranking layers, and LLM-augmented pipelines. You will design MMoE and PLE architectures in PyTorch to isolate task conflicts across engagement objectives like Saves, Dwell Time, and Shares. You will apply MMR and Bayesian optimization for diversity, freshness,