Hello fast.ai community,
What’s the difference between stochastic gradient descent with restarts and cyclical learning rate in part 1 lecture video 1?
As per my knowledge these both methods are used to find optimal learning rate. Which one is more efficient?
Kindly guide me through the differences of both.