Machine Learning - Supervised Learning

This article explains what Supervised Learning is for Machine Learning.

What is Supervised Learning? #

Supervised learning is characterized by providing the learning algorithm with examples from which to learn. These examples include the correct outputs or labels ‘y’ for given inputs ‘x’. By observing these correct input-output pairs, the algorithm learns to make reasonably accurate predictions for the output based only on the input.

Types of Supervised Learning #

There are two main types of supervised learning:

Regression #

: In this type, the goal is to predict a number, and there are infinitely many possible numbers. For example, predicting the price of a house based on features like its size, location, and age.

Classification #

: In this type, the goal is to predict categories, and there are a small number of possible outputs. For example, determining whether an email is spam or not based on its content and sender.