Answer:
false i think.
Explanation:
Gradient Descent is more likely to reach a local minima. because starting at different points and just in general having a different starting point, will lead us to a different local minimum( aka the lowest point closest to the starting point). if alpha(the learning rate) is too large, gradient descent may fail to converge and may even diverge.
