Genetic Algorithm (GA) and Stochastic Gradient Descent (SGD) are well-known optimization methods and are used for learning in Neural Networks. There are various implementations of GA, however, most of them (e.g. Neat) are not directly comparable to SGD because these GA methods use point/localized mutations in their connections/weights. Geoffrey Hinton, in one of his videos…