What is continuous training versus continuous deployment?
PICTURE THIS: DATA SPLIT
Fit on train, tune on val, report on test once.
Simple meaning
Continuous training automatically retrains on new data when triggers fire.
WHY — CI/CD for ML instead of guessing?
Why interviewers care about CI/CD for ML:
contrast on CI/CD for ML, not two memorised paragraphs.
the developer, then one case where picking wrong hurts.
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:
- 1Continuous training automatically retrains
on new data when triggers fire.
- 2Continuous deployment automatically releases
a model that passed gates.
- 3You can retrain daily
yet still require a canary before 100 percent traffic.
- 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
Continuous training automatically retrains on new data when triggers fire. Continuous deployment automatically releases a model that passed gates.