For my first year Machine Learning course, I made a simple integration of a linear perceptron. An n number of datapoints can be generated. A random target function is defined. On one side of the function, sign = 1. On the other side of the line, sign = -1. The datapoints are labeled, according to their position relative to the target function. Using the labeled coordinates, the model then comes up with a hypothesis that approaches the target function.