, now that we have our data importedit' time to think about the neural network step -defining the neural network architecture the architecture of the neural network refers to elements such as the number of layers in the networkthe number of units in each layerand how the units are connected between layers as neural networks are loosely inspired by the workings of the human brainhere the term unit is used to represent what we would biologically think of as neuron like neurons passing signals around the brainunits take some values from previous units as inputperform computationand then pass on the new value as output to other units these units are layered to form the networkstarting at minimum with one layer for inputting valuesand one layer to output values the term hidden layer is used for all of the layers in between the input and output layersi those "hiddenfrom the real world different architectures can yield dramatically different resultsas the performance can be thought of as function of the architecture among other thingssuch as the parametersthe dataand the duration of training add the following lines of code to your file to store the number of units per layer in global variables this allows us to alter the network architecture in one placeand at the end of the tutorial you can test for yourself how different numbers of layers and units will impact the results of our model