Stochastic gradient descent

Stochastic gradient descent is a variant of gradient descent that updates parameters using small random subsets of the training data rather than the whole dataset, making training faster and more scalable.

Stochastic gradient descent sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.

Also called SGD, Mini-batch gradient descent.