6 Steps To Write Any Machine Learning Algorithm From Scratch: Perceptron Case Study

Writing an algorithm from scratch is a rewarding experience, providing you with that "ah ha!" moment where it finally clicks, and you understand what's really going on under the hood. Am I saying that even if you've implemented the algorithm before with scikit-learn, it's going to be easy to write from scratch? Some algorithms are just more complicated than others, so start with something simple, such as the single layer Perceptron. I'll walk you through a 6-step process to write algorithms from scratch, using the Perceptron as a case-study. This methodology can easily be translated to other machine learning algorithms. This goes back to what I originally stated.