Gradient descent
Gradient descent is a first-order iterative optimization algorithm that minimizes a loss function by iteratively adjusting model parameters in the direction of steepest descent. It is the mathematical engine that allows machine learning models to “learn” by systematically reducing the error between their predictions and actual results.