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Category: Technical Terms
Category: Technical Terms
A loss function measures how wrong an AI model's predictions are during training.
The loss function compares the model's guesses to the correct answers and calculates a score. Higher scores mean worse performance. The training process tries to minimize this score.
Different tasks use different loss functions - image recognition uses different measures than language translation.
Loss functions guide AI learning by defining what "better" means. Without them, AI systems wouldn't know if they're improving or getting worse.
Choosing the right loss function often determines whether an AI project succeeds.
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