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