loss function
A loss function is a mathematical function used in machine learning that measures the dissimilarity between predicted and actual values, helping to quantify the error or discrepancy in the learning process. Its primary purpose is to provide a numerical value that represents the extent of deviation between predicted outcomes and the ground truth, enabling the algorithm to optimize and improve its predictions during training.
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