Mid-level interview questionAsked at Reddit · interview write-up
Design a system that predicts how likely a user is to comment on a post, focusing on label definition, features and model choice.
Model answer
Label: did the user comment within a fixed window after a real impression, one actually viewed, so unseen posts aren't false negatives.
Features, taken as of impression time: user history and community affinity; post age, community, text embedding and comment velocity; author affinity; context. Start with gradient-boosted trees, then a multi-task network that learns comments alongside clicks and votes, since comments are sparse. Evaluate log loss, calibration and AUC, then comments per user online.
Practise the rest
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