Should you scale features before PCA?
PICTURE THIS: 1, 2, 2, 8
Simple meaning
Yes, unless the features already share a meaningful common unit.
WHY — PCA instead of guessing?
Why interviewers care about PCA:
who only read docs from people who shipped.
and tied to AI / ML work.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens step by step?
Before you speak the answer, walk the interviewer through these steps:
- 1Yes, unless the features
already share a meaningful common unit.
- 2Unscaled PCA follows the
largest-unit columns rather than the real structure.
- 3StandardScaler before PCA is
the default interview answer.
- 4Give an example
One tiny concrete case you can say aloud.
- 5Common mistake
What juniors usually get wrong.
- 6Close
When you pick this over the alternative.
EXAMPLE — See it in action
Here's a short line you can speak, broken into clear beats:
Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.
Key takeaway
Yes, unless the features already share a meaningful common unit. Unscaled PCA follows the largest-unit columns rather than the real structure.