Supervised learning is a cornerstone of machine learning where labeled data (data paired with the correct answer) is used to train a model to make predictions on unseen data.

Supervised learning is like teaching a child with examples.

You give a computer lots of labeled data (for instance, pictures labeled “cat” or “dog”), so it can learn what makes each category different.

Over time, the computer figures out the patterns in these labeled examples.

Then, when it sees new data—like a picture it’s never seen—it can guess the correct label based on what it learned.