Too big, it explodes. Too small, it crawls.

The learning rate, step by step: why one number decides whether training works at all. Backpropagation tells every weight which way to move: its gradient. It doesn't say how far. That's the job of the learning rate, written η (eta). Every step of gradient descent is w ← w − η ∇L The gradient comes from the model. The learning rate is a setting you choose, and it is the first one people tune. This…