The learning rate controls the step size the model takes each time it adjusts during gradient descent.
Imagine it like this: Remember walking blindfolded down a hill to find the bottom of the valley. The learning rate is the size of your steps. Take steps that are too big, and you might stumble past the bottom. Take tiny steps, and it takes forever to get there.
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