How are gradient descent and learning rate used in logistic regression?

$1$ point

Gradient descent takes increasingly bigger steps towards the minimum with each iteration.

Gradient descent will minimize learning rate to minimize the cost in fewer iterations.

We want to minimize the cost by maximizing the learning rate value.

Gradient descent specifies the steps to take in the current slope direction, learning rate is the step length.