We build aseries of multi-layer perceptrons to classify Iris data by changing the model's hyperparameters.

We illustrate the basic perceptron algorithm to classify Iris flowers into 'Setosa' and 'not Setosa'. The problem and the features are chosen so that a linear classification boundary is possible. The purpose of the exercise is only to show how a perceptron works.