The Curse of Dimensionality 🧩

Here’s something that trips up many beginners:
More features ≠ always better.

When your dataset has too many features (dimensions), weird things happen:

⛔️ Distances between points become meaningless.
⛔️ Models struggle to generalize.
⛔️Training time explodes.

👉 Solution: techniques like PCA, feature selection, or just collecting smarter data instead of more data.

Remember: Adding noise isn’t adding information.