EXPLORING GRADIENT DESCENT IN MACHINE LEARNING

Gradient descent serves as a fundamental technique in machine learning. It facilitates models to optimize their parameters by iteratively reducing the error. This process involves determining the gradient of the objective function, which highlights the direction of steepest ascent. By shifting the parameters in the contrary direction of the gradien