Fix Prettier docs issues (#17798)
Signed-off-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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@ -153,7 +153,8 @@ Ultralytics collects three primary types of data using Google Analytics:
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- **Usage Metrics**: These include how often and in what ways the YOLO Python package is used, preferred features, and typical command-line arguments.
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- **System Information**: General non-identifiable information about the computing environments where the package is run.
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- **Performance Data**: Metrics related to the performance of models during training, validation, and inference.
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This data helps us enhance user experience and optimize software performance. Learn more in the [Anonymized Google Analytics](#anonymized-google-analytics) section.
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This data helps us enhance user experience and optimize software performance. Learn more in the [Anonymized Google Analytics](#anonymized-google-analytics) section.
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### How can I disable data collection in the Ultralytics YOLO package?
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@ -17,7 +17,7 @@ We utilize [Snyk](https://snyk.io/advisor/python/ultralytics) to conduct compreh
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Our security strategy includes GitHub's [CodeQL](https://docs.github.com/en/code-security/code-scanning/introduction-to-code-scanning/about-code-scanning-with-codeql) scanning. CodeQL delves deep into our codebase, identifying complex vulnerabilities like SQL injection and XSS by analyzing the code's semantic structure. This advanced level of analysis ensures early detection and resolution of potential security risks.
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[](https://github.com/ultralytics/ultralytics/actions/workflows/codeql.yaml)
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[](https://github.com/ultralytics/ultralytics/actions/workflows/github-code-scanning/codeql)
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## GitHub Dependabot Alerts
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