Easy Overfitting Question 10 of 223

What is underfitting?

AI & Data Analytics · Speak this in 60–90 seconds · Faridabad & Delhi NCR

Mean3.25average

Median2middle

Mode2most often

Underfitting means the model is too simple or poorly trained to capture the signal.

Why interviewers care about Overfitting:

Overfitting questions separate people

who only read docs from people who shipped.

Keep it short, concrete,

and tied to AI / ML 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.

Before you speak the answer, walk the interviewer through these steps:

1
Underfitting means the model
is too simple or poorly trained to capture the signal.
2
Both training error and
validation error stay high.
3
You usually add useful
features, pick a more flexible model, or fix an optimization problem such as too few epochs.
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.

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

Say this line

“Both training error and validation error stay high.”

Break into beats

Bothtrainingerrorandvalidationerror

Speaking order

2987408337471632900

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

Underfitting means the model is too simple or poorly trained to capture the signal. Both training error and validation error stay high.