Implementing a simple function with a single-layer perceptron

Take a look at the following code snippet to implement a single function with a single-layer perceptron:

    import numpy as np
    import matplotlib.pyplot as plt
    plt.style.use('fivethirtyeight')
    from pprint import pprint
    %matplotlib inline
    from sklearn import datasets
    import matplotlib.pyplot as plt

Defining and graphing transfer function types

The learning properties of a neural network would not be very good with just the help of a univariate linear classifier. Even some mildly complex problems in machine learning involve multiple non-linear variables, so many variants were developed as replacements for the transfer functions of the perceptron.

In order to represent non-linear models, a number of different non-linear functions can be used in the activation function. This implies changes in the way the neurons will react to changes in the input variables. In the following sections, we will define the main different...