Translations:Stochastic Gradient Descent/1/en

Stochastic gradient descent (often abbreviated SGD) is an iterative optimisation algorithm used to minimise an objective function written as a sum of differentiable sub-functions. It is the workhorse behind modern machine-learning training, powering everything from logistic regression to deep neural networks.