EXPLORING GRADIENT DESCENT IN MACHINE LEARNING

Gradient descent is a fundamental algorithm in machine learning. It aids models to adjust their parameters by iteratively decreasing the loss function. This process involves determining the gradient of the error metric, which signals the direction of steepest ascent. By moving the parameters in the inverse direction of the gradient, the model finds