Loss curves visually track a model's error over training iterations, revealing learning progress and potential overfitting. Machine learning engineers and data scientists use them to diagnose performance, adjust hyperparameters, and compare algorithms. This critical diagnostic tool helps practitioners optimize neural networks, improve predictive accuracy, and ensure robust model generalization.
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