What is the gradient descent algorithm?

Can you explain what the gradient descent algorithm is?

Sure! The gradient descent algorithm is an optimization technique used to minimize a function by iteratively moving towards the steepest descent.

How does it work in machine learning?

In machine learning, gradient descent helps in minimizing the loss function, allowing models to learn from data by adjusting parameters.

What are the different types of gradient descent?

There are several types, including batch gradient descent, stochastic gradient descent, and mini-batch gradient descent, each with its own use cases.

What are the advantages and disadvantages of using it?

Advantages include simplicity and efficiency, while disadvantages can be getting stuck in local minima and sensitivity to learning rates.