How does gradient descent work in machine learning?

How does gradient descent work in machine learning?

Gradient descent is an optimization algorithm used to minimize the loss function in machine learning models by iteratively adjusting parameters.

Can you explain how to visualize gradient descent?

Sure! You can visualize gradient descent by plotting the loss function and showing how the algorithm moves towards the minimum point.

What tools can I use to visualize it?

You can use libraries like Matplotlib in Python to create visualizations of gradient descent, showing the path taken by the algorithm.

Are there different types of gradient descent?

Yes, there are several types, including batch gradient descent, stochastic gradient descent, and mini-batch gradient descent, each with its own characteristics.