EXPLORING GRADIENT DESCENT IN MACHINE LEARNING

Gradient descent serves as a fundamental technique in machine learning. It enables models to refine their parameters by iteratively reducing the loss function. This approach involves determining the gradient of the error metric, which signals the direction of steepest ascent. By shifting the parameters in the contrary direction of the gradient, the