Gradient Descent
Gradient descent optimizes AI models by minimizing the loss function, guiding the learning process towards better predictions.
Gradient descent is an optimization algorithm used in training machine learning models. It minimizes a function by iteratively moving in the direction of the steepest descent, calculated by the negative of the gradient. This process helps in adjusting model parameters (weights) to minimize the loss function and improve the model's predictions.