Backpropagation, Neural Networks.
there, because w is equal to a row vector. In the case of logistic regression with the single output, dw² is like that, whereas w here was a column vector. That’s why there’s an extra transpose for a¹, whereas we didn’t for x here for logistic regression. This completes half of backpropagation.