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Gradient descent serves as a fundamental algorithm in machine learning. It aids models to refine their parameters by iteratively decreasing the loss function. This process involves calculating the gradient of the error metric, which signals the direction of steepest ascent. By shifting the parameters in the opposite direction of the gradient, the m