Supervised Learning

What is supervised learning?

Supervised learning is a type of machine learning algorithm that involves learning from a set of training data that has been labeled with the correct answers. The algorithm is "supervised" because it is given this training data, which tells it what the correct answers are. It then uses this information to learn how to predict the correct answer for new data.

The computer system is "trained" with a set of example inputs and corresponding desired outputs, allowing it to learn how to produce the desired outputs for new inputs.

ELI5: Explain supervised learning like I’m 5 years old

Sure, let's imagine you're learning to identify different types of fruits.

Your mom shows you an apple and says, "This is an apple." Then, she shows you a banana and says, "This is a banana." She does this with several different types of fruits. After a while, you start to recognize the fruits on your own. If she holds up an apple, you can say, "That's an apple!" And if she holds up a banana, you can say, "That's a banana!"

This is a lot like supervised learning in machine learning. The computer (or model) is like you, and the person teaching it is like your mom. The model is shown examples (like the fruits) and the correct answers (like the names of the fruits). After seeing many examples, the model can start to identify the correct answers on its own.

So, in supervised learning, the model learns from examples with correct answers, just like you learned to identify fruits by seeing them and hearing their names.