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Co-authored-by: Ilya Mashchenko <ilya@netdata.cloud>
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# Machine Learning and Anomaly Detection
Netdata provides a variety of Machine Learning features to help you troubleshoot certain scenarios that might come up.
Netdata provides advanced Machine Learning features to help you identify and troubleshoot anomalies and unexpected behavior in your infrastructure before they become critical issues:
- K-means clustering [Machine Learning models](/src/ml/README.md) are trained to power the [Anomaly Advisor](/docs/dashboards-and-charts/anomaly-advisor-tab.md) on the dashboard, which allows you to identify anomalies in your infrastructure
- [Metric Correlations](/docs/metric-correlations.md) are possible through the dashboard using the [Two-sample Kolmogorov Smirnov](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test#Two-sample_Kolmogorov%E2%80%93Smirnov_test) statistical test and Volume heuristic measures
- The [Netdata Assistant](/docs/netdata-assistant.md) is able to answer your prompts when it comes to troubleshooting alerts and anomalies.
- K-means clustering [Machine Learning models](/src/ml/README.md) are trained to power the [Anomaly Advisor](/docs/dashboards-and-charts/anomaly-advisor-tab.md) on the dashboard, which allows you to identify Anomalies in your infrastructure.
- [Metric Correlations](/docs/metric-correlations.md) are possible through the dashboard using the [Two-sample Kolmogorov Smirnov](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test#Two-sample_Kolmogorov%E2%80%93Smirnov_test) statistical test and Volume heuristic measures.
- The [Netdata Assistant](/docs/netdata-assistant.md) is able to answer your prompts when it comes to troubleshooting Alerts and Anomalies.

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# Maintenance operations on Netdata Agents Overview
This section provides information on various actions you can take when maintaining a Netdata Agent.
This section provides information on various actions you can take while maintaining a Netdata Agent.
- [Starting and Stopping Netdata Agents](/docs/netdata-agent/start-stop-restart.md)
- [Update Netdata Agents](/packaging/installer/UPDATE.md)
- [Reinstall Netdata Agents](/packaging/installer/REINSTALL.md)
- [Uninstall Netdata Agents](/packaging/installer/UNINSTALL.md)

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# Working with Logs
This section talks about ways Netdata collects and visualizes logs, while also providing useful guides on log centralization setups that can be used with Netdata.
This section talks about ways Netdata collects and visualizes logs.
The [systemd journal plugin](/src/collectors/systemd-journal.plugin/) is the core Netdata component for reading systemd journal logs.
For structured logs, Netdata provides tools like [log2journal](/src/collectors/log2journal/README.md) and [systemd-cat-native](/src/libnetdata/log/systemd-cat-native.md) to convert them into compatible systemd journal entries.
You can also find useful guides on how to set up log centralization points in the [Observability Cetralization Points](/docs/observability-centralization-points/README.md) section of our docs.