So I understand what "layers" are. If you have 5 layers in your model, your data basically gets transformed 5 times via 5 activation functions. The number of "neurons" within a layer dictate how many outputs a layer creates.
So what are "cells"? I never understood where "cells" come into play. Are they a collection of layers?
Per Wiki: https://en.wikipedia.org/wiki/Long_short-term_memory
If the orange are layers, then I would imagine each has a bunch of neurons. So a cell is a collection of layers and yellow stuff? I'm having trouble understanding where this "cell" fits into an overall NN architecture. I am used to the pictures with input layer -> hidden layer -> output layer. So where would the "cell" occur?