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18 March 2023

  • curprev 13:1913:19, 18 March 2023‎ Walle talk contribs‎ 3,549 bytes +3,549‎ Created page with "{{see also|Machine learning terms}} ==Introduction== In the field of machine learning, ''loss'' refers to a quantitative measure of the discrepancy between a model's predicted outputs and the true or observed values. It serves as an evaluation metric to assess the performance of a machine learning algorithm during the training process. By minimizing the loss function, practitioners aim to improve the model's accuracy and generalization capabilities. ==Loss Functions..."
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