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- user: I still do not get why gradient descent needs a learning rate.
- agent: Picture walking downhill in fog. The gradient tells you which way is down; the learning rate is how big a step you take. Too big and you leap over the valley. Want to see that?
- user: Yes.
- agent: Same 20 steps at three rates. The middle one settles; the large one oscillates forever. Now you: which would you pick for a narrow valley?