Discovering the Magic of Deep Learning: How Computers Learn Like Humans!

STEM Education and in-depth topics to share with you! Deep learning is a type of computer program that helps machines learn to do things like humans do. Imagine you're teaching a robot how to play a game of tag. You would need to give the robot some rules to follow, like "you can't tag someone who is already 'it'," or "you can only tag someone who is within arm's reach." Deep learning works similarly. Instead of giving robot rules to follow, though, we give a computer program a lot of examples of things that we want it to learn. For example, we might give the program lots of pictures of cats and dogs, and tell it which ones are cats and which ones are dogs. The program uses these examples to learn how to tell the difference between a cat and a dog. The reason it's called "deep" learning is because the program uses lots of layers to learn. Think of each layer as a step in the learning process. The first layer might look at the picture of the cat and try to identify the basic shapes that make up the cat's body. The next layer might look at the shapes and try to identify parts of the cat, like its tail or its ears. And so on, until the program can accurately identify whether the picture is of a cat or a dog. Deep learning is used in lots of different ways. For example, it's used to help self-driving cars "see" the world around them and make decisions about where to go. It's also used to help doctors diagnose diseases by looking at medical images, like X-rays or MRIs. One thing that's cool about deep learning is that the more examples it sees, the better it gets at learning. Just like you get better at tag the more times you play, a deep learning program gets better at identifying cats and dogs the more pictures of cats and dogs it sees. So that's deep learning in a nutshell! It's a way for computers to learn by example, using lots of layers to gradually get better at whatever task we want them to learn.