Supervised learning algorithms can be further subdivided into regression and classification. In supervised tasks, we present the computer with a collection of labeled data points called a training set (for example a set of readouts from a system of train terminals and markers where they had delays in the last three months). Trying everything is impractical to do manually, so of course machine learning tool providers have put a lot of effort into releasing AutoML systems. The problem is that it can only do what it is trained to do including all the implicit errors built into the dirty data… Read More