Loss functions measure the difference between predicted and actual values in machine learning models. They guide the optimization process during training to minimize error.
Inside Loss Functions (1)
Binary Cross-Entropy — Binary cross-entropy is a loss function used for binary classification tasks, quantifying the difference between true labels and predicted probabilities.
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