What are some applications of iterative algorithms?

What are some applications of iterative algorithms?

Iterative algorithms are widely used in optimization problems, numerical analysis, and machine learning. For example, they help in finding the minimum of a function or solving systems of equations.

Can you give me a specific example in machine learning?

Sure! In machine learning, iterative algorithms like gradient descent are used to minimize the loss function during the training of models.

How does gradient descent work?

Gradient descent works by iteratively adjusting the model parameters in the direction of the steepest decrease of the loss function, using the gradient.

What are the advantages of using iterative algorithms?

The advantages include efficiency in handling large datasets, flexibility in optimization, and the ability to converge to a solution even with complex functions.