This question evaluates competency in end-to-end real-time ML system design for personalized ad selection, including model decisioning, feature engineering and stores, exploration–exploitation strategies, offline and online evaluation, and scalability and latency constraints within the Machine Learning domain.
You need to design a real-time, data-driven ad selection system that personalizes ads for millions of users. Assume:
Design an end-to-end ML system to select ads at request time. Discuss and justify:
Hints: CTR prediction with logistic regression or GBDT; counterfactual evaluation (IPS/DR); feature store for train-serve consistency; bandits for exploration.
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