How does CI/CD apply to ML projects?
PICTURE THIS: DATA SPLIT
Fit on train, tune on val, report on test once.
Simple meaning
CI runs tests on code and sometimes data validation.
WHY — CI/CD instead of guessing?
Why interviewers care about CI/CD:
question about CI/CD.
trade-offs, and what you would actually do on a MLOps project - not buzzwords.
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:
- 1CI runs tests on
code and sometimes data validation.
- 2CD deploys models or
pipelines with approval gates.
- 3I version both code
and model artifacts together.
- 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
CI runs tests on code and sometimes data validation. CD deploys models or pipelines with approval gates.