Term
Model Monitoring
Definition
Model monitoring is the process of keeping an eye on an AI model's performance and reliability once it's up and running. It ensures that the model continues to work correctly and make accurate predictions.
Where you’ll find it
You can find model monitoring tools typically in the dashboard or monitoring section of the AI platform.
Common use cases
- Ensuring that the AI model is performing as expected over time.
- Detecting and addressing any decline in model performance.
- Supporting decisions around model improvements or updates.
Things to watch out for
- Complex metrics that may require a deeper understanding to interpret correctly.
- Not all AI platforms support real-time monitoring; some may have delays.
- Integration issues with other systems or tools.
Related terms
- Performance Metrics
- AI Deployment
- Retraining
- Predictive Accuracy
- Dashboard
Pixelhaze Tip: Always set up alerts within your model monitoring tools. These can notify you if there's a significant change in the model's performance, allowing you to address issues before they significantly affect outcomes. This proactive approach can save a lot of troubleshooting time down the line.