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How do you choose a loss function (MSE, MAE, Huber, cross-entropy, focal, contrastive)?

The loss defines what the model optimizes, and picking the wrong one quietly dooms it. The signal is matching the loss to the task and data (outliers, imbalance), not defaulting to MSE or cross-entropy on reflex.

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

The loss defines what the model optimizes, and picking the wrong one quietly dooms it. The signal is matching the loss to the task and data (outliers, imbalance), not defaulting to MSE or cross-entropy on reflex.

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