Learning Rate Explorer

The learning rate is the single most important hyperparameter in gradient descent. Too small and your model crawls toward the minimum over thousands of iterations. Too large and it overshoots, oscillates, or explodes into NaN. Your mission: run the same gradient descent algorithm with four different learning rates and plot the results on one chart. See the difference for yourself.