What is Supervised and Unsupervised Learning in AI? Explained in Everyday Language for Absolute AI Beginners

I assume you’ve already come across basic machine learning terms while exploring AI, including supervised and unsupervised learning. Then, ou might be wondering exactly what the differences are and when to apply each. So in this blog, we will introduce the two terms and break them down.

First of all, about the role of machine learning in AI

Supervised Learning and Unsupervised Learning are two fundamental approaches in machine learning, where machine learning is a subset of the concept of AI. In this sense, all machine learning is AI, but not all AI is machine learning. Machine learning represents a key way by which modern AI systems achieve intelligent behavior, particularly in applications involving large amounts of data and predictions based on that data.

I believe there are plenty of articles and courses out there that explain machine learning. However, to reintroduce the term, you can simply think of machine learning as a set of frameworks or methods that enable machines to learn certain patterns. Then, in this way, supervised learning and unsupervised learning are THE ways that describe how a “machine” (aka a computer program) learns.