8 Clustering Algorithms in Machine Learning that All Data Scientists Should Know

There are three different approaches to machine learning, depending on the data you have. You can go with supervised learning, semi-supervised learning, or unsupervised learning. In supervised learning you have labeled data, so you have outputs that you know for sure are the correct values for your inputs. That's like knowing car prices based on features like make, model, style, drivetrain, and other attributes. With semi-supervised learning, you have a large data set where some of the data is labeled but most of it isn't. This covers a large amount of real world data because it can be expensive to get an expert to label every data point.