What are Local Minima and Global Minima in Gradient Descent?

Ans: Local minima:

The point in a curve which is minimum when compared to its preceding and succeeding points is called local minima.

Global minima:

The point in a curve which is minimum when compared to all points in the curve is called Global Minima.

For a curve there can be more than one local minima, but it does have only one global minima.

In gradient descent we use this local and global minima in order to decrease the loss functions.