The mathmatics of the perceptron

I have been learning about machine learning for some time now and I believe that, to really understand something, one must understand the basics. In this blog post I will go through the theory and at the end I'll share the code for a perceptron, the most basic neural network there is that dates back to 1958 created by Frank Rosenblatt. To train and test it, I'll use a fragment of the mnist dataset. This dataset contains images of 28 x 28 pixels of hand-written digits from 0 to 9. We'll try to classify two, four and six digits and see that it becomes increasingly more difficult to make predictions. The concept of the perceptron is that, with only a simple layer of calculations, our code can understand rules and paths without explicitlly writing them.