Loops are like the ultimate party trick of the Neural Network world. They're like the spinning top of algorithms, the spinning wheel of logic, the... okay, you get it.
But seriously, a loop is just a fancy way of saying "we're going to do this thing over and over again until we get it right". Like, imagine you're trying to find the perfect burrito. You taste it, you spit it out, you try again, and again, and again... until it's just right.
Loops are like that, but with code. And instead ofประก burritos, we're talking about neural networks and stuff.
Want to learn more about loops? What is an Activation Function?
Or maybe you're more of a "get to the point" kind of person? In that case, How Do Neural Networks Learn?
Loops are like the never-ending staircase to understanding Neural Networks. You can keep climbing, keep learning, keep looping... until you reach the top.
But don't worry, it's not all doom and gloom. We've got some loopy tunes to keep you company on your journey.