Gradient Descent, Neural Networks.
B1, W2, and B2. So, as a reminder, if you have NX or alternatively N0 input features, and N1 hidden units, and N2 output units in our examples. So far I’ve only had N2 equals one, then the matrix W1 will be N1 by N0. B1 will be an N1 dimensional vector, so we can write that as N1 by one-dimensional