EXPLORING GRADIENT DESCENT IN MACHINE LEARNING

Gradient descent plays the role of a fundamental technique in machine learning. It enables models to adjust their parameters by iteratively minimizing the error. This approach involves estimating the gradient of the objective function, which indicates the direction of steepest ascent. By moving the parameters in the inverse direction of the gradien