Learn Python by Building Data Science Applications

Moving on to supervised learning

Now, let's try supervised learning. As we discussed earlier, supervised models are designed to predict, or estimate, target variables—either a continuous value (regression problem) or a specific category (classification problem). Other types of problems (tagging, semantic segmentation, and many more)—can then be defined as one of those two. Let's glance over a suite of relatively simple models now.

One simple yet often pretty performant model is the k-nearest neighbors (KNN) algorithm. It is quite similar to k-means, as it also performs in Euclidean space.