You know how it feels when you overcook your dinner, but can't stop adding more salt because you're convinced it'll magically fix the flavor? That's overfitting, folks!
When you overfit, you're like a chef trying to perfect the perfect soufflé, but your AI model is just a soggy disaster.
In machine learning, overfitting is when your model is too good at its job, but only on the training data. It's like your AI is a supermodel who's too good at recognizing your aunt's face, but can't tell a stranger from a cat.
So, how do you avoid overfitting? It's simple: Regularization is like a recipe with less salt.
Want to learn more about regularization? Click here.