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You need a model but only have a few hundred labeled examples. How do you build one anyway?

Small labeled sets are the normal starting condition, not an excuse. The strong answer is a ladder of techniques that squeeze signal from unlabeled data, pretrained models, and the labeling budget. Here it is.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Small labeled sets are the normal starting condition, not an excuse. The strong answer is a ladder of techniques that squeeze signal from unlabeled data, pretrained models, and the labeling budget. Here it is.

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