How models actually learn, from vanilla gradient descent to Adam
Adam combines two ideas: momentum for the average gradient, and RMSProp-style scaling for the average squared gradient. It then corrects early bias because those moving averages start at zero.
🔒 This is a Pro lesson — the interactive figure, worked examples, quiz and practice open with Pro access.
▶ Adam