Back Propagation Vs Learning rate in Neuralnet Optimisation
Using backpropagation is nothing else than performing (stochastic) gradient descent.
It computes the gradient, but it is  not the &quot;optimal&quot; weight. The gradient is used to update the current weight (according to the gradient descent algorithm).
The gradient descent algorithm needs a step size (which is called learning rate in the context of machine learning).
The step size defines how &quot;strong&quot; the current weights are updated by the current gradient.