Deep learning is a type of machine learning that helps computers learn and understand complex things, like pictures, sounds, and words. Imagine you're trying to teach a child to recognize different animals.
At first, the child might not know what a cat or dog looks like. But if you show them many pictures of cats and dogs, they'll start to notice patterns and differences. They might notice that cats have pointy ears and dogs have floppy ears.
Deep learning works in a similar way. It's like a big stack of layers that help the computer learn and understand complex things. Each layer looks at the information and tries to find patterns or features.
For example, if we're trying to teach a computer to recognize pictures of cats and dogs, the first layer might look at the edges in the picture. The next layer might look at the shapes and textures. The next layer might look at the features like ears, eyes, and nose.
As the information goes through more and more layers, the computer starts to understand what makes a cat a cat and what makes a dog a dog. It's like the computer is building a big puzzle, and each layer helps it get closer to the final picture.
Deep learning is powerful because it can learn from big datasets and make accurate predictions. It's used in many applications, like self-driving cars, facial recognition, and virtual assistants.
