In this article, we focus on the notion of supervised machine learning and its associated categories. We briefly discuss the popular categories and algorithms without digging too much into detail. The goal is to have an idea of what is supervised learning.
In this article, we outline different steps to define, frame, organize, deploy, and evaluate a successful Machine Learning (ML) project. The expected audience for this article involves business stakeholders, supervisors, Machine Learning experts, and software development engineers.