What is Supervised Learning?

Think of supervised learning like teaching a child using flashcards. You show a flashcard with a picture of an apple and say “This is an apple.” You show another with a banana and say “This is a banana.” After seeing enough examples, the child learns to recognise apples and bananas on their own.

That’s supervised learning: we provide the data and the correct answer (label) for the computer to learn from.

Example:

Imagine you have a bunch of emails. Some are spam, some are not spam. You mark each email clearly (label it) as “spam” or “not spam” and then give this data to the computer. The computer learns the difference based on your examples. Next time a new email comes in, it can guess whether it's spam or not.

Summary:

1. You provide both data and the correct answer.
2. The computer learns from labeled examples.
3. Used in tasks like email filtering, face recognition, and medical diagnosis.

What is Unsupervised Learning?

Now, imagine you give a child a basket of fruits — apples, bananas, and oranges — without telling what they are. The child might group the fruits by shape, color, or size on their own. That’s unsupervised learning: the computer looks at data and tries to find patterns or groupings without any labels.

Example:

Let’s say you run a clothing store and have data on customer purchases. You don’t know anything about the customers, but you want to group similar shoppers. You use unsupervised learning, and the computer finds:

1. One group buys mostly kids’ clothes.
2. Another buys luxury fashion.
3. Another buys gym wear.

Now you can create offers for each group — even though you never told the computer what those groups should be!

Summary:

1. You provide only the data, no labels or correct answers.
2. The computer finds patterns on its own.
3. Used in tasks like customer segmentation, product recommendations, and market research.

Published :12:53 AM - 03 May 2025