Question: why sgd better than adam?
Answer: SGD is a variant of gradient descent. Instead of performing computations on the whole dataset — which is redundant and inefficient — SGD only computes on a small subset or random selection of data examples. ... Essentially Adam is an algorithm for gradient-based optimization of stochastic objective functions.