Gradient Accumulation

How models actually learn, from vanilla gradient descent to Adam

Gradient accumulation simulates a larger batch when memory is limited. Instead of stepping after every micro-batch, you add gradients from several micro-batches, then take one optimizer step.

🔒 This is a Pro lesson — the interactive figure, worked examples, quiz and practice open with Pro access.

▶ Gradient Accumulation
← Batch Size ScalingInitialization & Signal Scale →