Does gradient descent methods always converge to same point

Question

Hi!!

I'm new to machine learning and I want to know if gradient descent always converges to the same point?

Answer 1

No, they always don't. That's because in some cases it reaches a local minima or a local optima point. 

So, you always don’t reach the global optima point. It depends on the data and starting conditions