Why isn't the neural network updated after every example in the dataset Why the neural network is updating only after the whole batch passes?
Weights get updated based on the number of examples you feed in a batch. This is because, a full pass(forward and backward) of matrix computations has to be completed in order for the weights to be updated, after back-propagation and proceeding with next epoch, with batch type you had chose.
Moreover, If you use stochastic gradient descent, where each example will be processed at a time, your weights will updated after having processed every example.