Gradient descent is a fundamental method in machine learning. It aids models to adjust their parameters by iteratively minimizing the loss function. This strategy involves estimating the gradient of the objective function, which highlights the direction of steepest ascent. By shifting the parameters in the opposite direction of the gradient, the mo