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Model parameters are internal variables in a machine learning model that are learned and determined during training using the provided data. These parameters are critical for the model’s predictive capability, as their values define how the model processes inputs to generate outputs. They are adjusted during training to minimize errors and optimize performance, enabling the model to fit the data and make accurate predictions.