Let's say you're learning to sort your toys.
In supervised learning, your mom or dad is there to guide you. They show you which toys are cars, which are dolls, and which are blocks. You learn by their guidance. If you make a mistake, they correct you. Over time, you learn to sort your toys correctly because you've been taught the right categories. 💻
Unsupervised learning is like if you were left to sort your toys on your own. No one tells you what the categories are. You might decide to sort them by color, by size, or by how much you like them. You're not sure if you're doing it "right" because no one is there to correct you, but you're learning to find patterns and make sense of your toys on your own. 💻
So, in simple terms, supervised learning is when the computer is taught with correct answers (like your parents teaching you how to sort toys), and unsupervised learning is when the computer has to figure out the patterns on its own (like you sorting toys without any guidance).
Imagine you're learning to color. You have a coloring book with outlines of different objects - trees, houses, cars, and so on.
Supervised learning is like having your older sibling or parent sitting next to you while you color. They already know what color each object should be. They tell you "This is a tree, it should be green" or "This is a car, it should be red". You're learning to color the right way because they're guiding you and telling you the correct colors for each object.
In the same way, in supervised learning, a computer program is learning to make predictions from data. But it's not doing it alone - it has a 'teacher' (the data scientist) who provides it with the correct answers for some examples. The program uses these examples to learn and make accurate predictions for new data.
Imagine you have a big box of Lego blocks of different shapes, sizes, and colors. No one tells you what to do with them. So, you start sorting them out yourself. Maybe you group them by color, or by size, or by shape. You're not sure if you're doing it "right" because no one is there to correct you, but you're learning to find patterns and make sense of the blocks on your own.
That's what unsupervised learning is like in machine learning. The computer is given a lot of data but no instructions on what to do with it. It has to figure out how to organize the data on its own, maybe by finding groups or patterns in the data. It's like sorting Lego blocks without any guidance. 💻