model-monitoring

Vocabulary Word

Definition

'Model monitoring' is a lot like a gym coach who's keeping eye on your workouts. Here, it refers to observing and evaluating the performance of the machine learning models.

Examples in Different Contexts

In data science, 'model monitoring' helps ensure models perform as expected after deployment. A data scientist might explain, 'We use model monitoring to catch any drift in data patterns that might affect model accuracy.'

Practice Scenarios

Scenario:

We need to take immediate action. The drift in our prediction model's performance could critically affect our project's results.

Response:

Absolutely, enacting a stringent model monitoring system will help us identify and handle the drift.

Business

Scenario:

Recently, our predictions about loan defaults have been a bit off. It seems the model cannot handle the increasing complexity of data.

Response:

I think it's best if we start model monitoring to examine the risk model's predictive accuracy.