A loss function is a mathematical tool used to measure how well a machine learning model's predictions match the actual data. It quantifies the difference between predicted outcomes and actual results, guiding the optimization process during model training. The ultimate goal is to minimize this loss, helping the model to learn and improve its performance over time.
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