Matrix, Dimensions.
layers here, four hidden layers and one output layer. If you implement forward propagation, the first step will be Z1 equals W1 times the input features x plus b1. Let’s ignore the bias terms B for now and focus on the parameters W. Now, this first hidden layer has three hidden units. So this is