Introduction to supervised learning setup 3.2 Regression and Classification in machine learning

Okay! So, supervised learning is like when a teacher is helping you learn something new. In this case, a computer is the teacher and it’s trying to learn from some examples that we give it. Regression and Classification are two types of things that a computer can learn in machine learning. Regression is like trying to predict a number, such as how tall someone will be based on their age. Classification is like sorting things into different categories, such as deciding if a picture is of a cat or a dog. For example, let’s say we want the computer to learn how to predict the price of a house based on its size. This would be a regression problem. The computer would look at a bunch of houses and their prices and try to figure out a pattern. On the other hand, if we want the computer to learn how to classify emails as either spam or not spam, that would be a classification problem. The computer would need to look at lots of emails and learn what features indicate that an email is spam. One interesting fact about machine learning is that it is being used in self-driving cars to help them make decisions on the road. The cars use machine learning algorithms to analyze data from sensors and cameras to navigate safely. I hope that helps you understand a little bit about supervised learning, regression and classification in machine learning!