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Gradient descent is a fundamental technique in machine learning. It facilitates models to adjust their parameters by iteratively minimizing the error. This process involves calculating the gradient of the objective function, which highlights the direction of steepest ascent. By moving the parameters in the contrary direction of the gradient, the mo