Calculus, Derivatives, Limits, Machine Learning, Data Science.
that minimizes the cost function. Gradient Descent: This optimization algorithm relies heavily on calculus. The gradient of the cost function with respect to the model parameters indicates the direction of steepest ascent. By taking steps in the opposite direction (i.e., descending the gradient),