Dimensionality reduction

Dimensionality reduction is like cleaning up a messy room. You have a lot of stuff in the room that you don't need, and the room seems overwhelming. So you take out all the things you don't need, like old toys and clothes that don't fit you anymore, and throw them away. Now your room is less cluttered, and it's easier to find the things you want.

In data science, dimensionality reduction is like cleaning up a messy dataset. You often have a lot of columns (like toys in your messy room) that aren't necessary and that can cloud your view of the important data. Removing those columns (like throwing away the old toys) can help you make better sense of the data by focusing on what is important. Removing unnecessary columns also makes it easier for the computer to understand your data.