Counting the number of layers in a neural network I am going over the Udacity tutorial on Neural Networks.  

Here's a diagram from the tutorial:  



What makes this a '2 layer neural network'?  


I was under the impression that the first layer, the actual input, should be considered a layer and included in the count.  
This screenshot shows 2 matrix multiplies and 1 layer of ReLu's. To me this looks like 3 layers. There are arrows pointing from one to another, indicating they are separate. Include the input layer, and this looks like a 4 layer NN.
This is a 2-layer network because it has a single hidden layer and an output layer. We don't count the first layer. When we say 3 layers, we actually mean 2 hidden layers and an output layer. Perhaps this helps you?

EDIT: We don't count the input layer because there's no parameter (bias + weights). In actual implementation, it's not implemented. Netural network framework simply "connects" the input features to the first adjustable layer (eg: hidden layer).