82Your training data was collected with selection bias. How do you detect it and correct for it?▼hardMetaAmazonGoogle1 replies◆ premiumWhen labels exist only for the cases you already acted on, the model learns a distorted world: strong offline, blind to everyone you never saw. Worse, its own decisions choose the next labels. Here is how to spot it and counter it.Open full answer →
04Predict watch time for items in a video catalog, Netflix-style. How do you build it?▼hardNetflixYouTubeDisney+unlockedWatch time is the label everyone optimizes and hardly anyone measures cleanly. You see minutes only for videos people chose to play, the distribution is savagely skewed, and the slot they saw it in shifted the number. The interview asks whether you can predict a biased label honestly.Open full answer →