data set of interest and we're going to think of the neurons representation what it's learned as what we call an activation vector so we feed in this kind of data set of interest and this neuron is going to emit a scalar value across all of these these input points and we can literally just sort of stack all of these and that'll form a vector that we call the the activation vector of this neuron and so there's this sort of nice framework where we kind of think of these neurons as these activation vectors and because layers are linearly