Deep Neural Networks, Forward Propagation.
input data. Neural Networks and Deep Learning But given a single training example x, here’s how you compute the activations of the first layer. So for this first layer, you compute z1 equals w1 times x plus b1. So w1 and b1 are the parameters that affect the activations in layer one. This is layer