being a dense layer one other note when classifying something into only two categories we could get by with only one node at the output in this case a prediction of how urban a photo is would also be a measure of how rural it is if a photo is 80 percent likely to be urban its twenty percent likely to be rural but we've kept two separate nodes at the output layer using a separate node for each possible category in the output layer will help us transition into cases when we want to predict with more than two categories in both the current case