Little Bits of Artificial Intelligence

1. Simple Explanation (Layman Style)

What’s the Problem?

When a neural network performs too well on training data but fails on unseen data, it’s called overfitting.

Imagine a student who memorizes all the questions and answers from the practice book — but during the real exam, struggles with even slightly different questions. That’s overfitting.

What’s the Solution?

We want the model to learn patterns, not just memorize.

That’s where regularization helps. It gently tells the model:

“Hey, don’t rely too heavily on any one path (weight) — keep it simple and balanced.”