Backpropagation, Mathematics, Calculus, Machine Learning, Neural Networks.
through our network to get to the second weights matrix. Even better, we can reuse the first two derivatives (since we still have to derive the cost and the last layer’s sigmoid activation to get to the first set of weights). Imagine the derivative on the left of the equal sign says θ1 instead of