EXPLORING GRADIENT DESCENT IN MACHINE LEARNING

Gradient descent is a fundamental method in machine learning. It aids models to adjust their parameters by iteratively reducing the cost. This strategy involves estimating the gradient of the objective function, which signals the direction of steepest ascent. By shifting the parameters in the inverse direction of the gradient, the model converges t