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PyCharm Docs Inspect fixes (#18432)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-12-29 23:19:05 +05:00 • committed by GitHub
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docs/en/guides/model-monitoring-and-maintenance.md
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@ -23,7 +23,7 @@ Regular model monitoring helps developers track the [model's performance](./mode
Here are some best practices to keep in mind while monitoring your computer vision model in production:
- **Track Performance Regularly**: Continuously monitor the model's performance to detect changes over time.
- **Double Check the Data Quality**: Check for missing values or anomalies in the data.
- **Double-Check the Data Quality**: Check for missing values or anomalies in the data.
- **Use Diverse Data Sources**: Monitor data from various sources to get a comprehensive view of the model's performance.
- **Combine Monitoring Techniques**: Use a mix of drift detection algorithms and rule-based approaches to identify a wide range of issues.
- **Monitor Inputs and Outputs**: Keep an eye on both the data the model processes and the results it produces to make sure everything is functioning correctly.