You are building a personalized recommendation system for a consumer digital content platform. Users browse, click, save, and consume items, and the product team wants ranked recommendations that adapt to each user’s interests while still working for new users and newly added items.
How would you approach building this recommendation system end to end, including the modeling strategy, feature design, training setup, evaluation, and how you would handle cold-start and production serving tradeoffs?