Gradient descent
Repeatedly moving the parameters a small step against the gradient to lower the loss: params ← params - η·∇L. It needs only a gradient, so it can train almost any model.
Repeatedly moving the parameters a small step against the gradient to lower the loss: params ← params - η·∇L. It needs only a gradient, so it can train almost any model.