Moderate Concept Drift Question 85 of 221

What is a feedback loop and how can it create apparent concept drift?

MLOps track · Speak this in 60–90 seconds · Faridabad & Delhi NCR

PICTURE THIS: DATA SPLIT

Train 70%Val 15%Test 15%

Fit on train, tune on val, report on test once.

Simple meaning

If the model’s scores change who gets a loan, future training data is selected by the previous model.

WHY — Concept Drift instead of guessing?

Why interviewers care about Concept Drift:

Concept Drift questions separate

people who only read docs from people who shipped.

Keep it short, concrete,

and tied to MLOps work.

Stay structured

Name the idea, why it exists, then one short example.

Close cleanly

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:

1
If the model’s scores
change who gets a loan, future training data is selected by the previous model.
2
That biased sample can
look like the world changed.
3
You mitigate with exploration,
logging rejected cases, or propensity methods, not only more trees.
4
Give an example
One tiny concrete case you can say aloud.
5
Common mistake
What juniors usually get wrong.
6
Close
When you pick this over the alternative.

EXAMPLE — See it in action

Here's a short line you can speak, broken into clear beats:

Say this line

“That biased sample can look like the world changed.”

Break into beats

Thatbiasedsamplecanlooklike

Speaking order

2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

Key takeaway

If the model’s scores change who gets a loan, future training data is selected by the previous model. That biased sample can look like the world changed.