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* initial setting up of notebook * add open in colab button * draft work * first version of notebook * fix open in colab button * Update ml/notebooks/README.md Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * use underscores in filename * add one final visualization approach using scatter plots * get a better random sample for plots * small text update * fix link * Update ml/notebooks/netdata_anomaly_detection_deepdive.ipynb Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * Update ml/notebooks/netdata_anomaly_detection_deepdive.ipynb Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * Update ml/notebooks/netdata_anomaly_detection_deepdive.ipynb Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * Update ml/notebooks/netdata_anomaly_detection_deepdive.ipynb Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * Update ml/notebooks/netdata_anomaly_detection_deepdive.ipynb Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * Update ml/notebooks/netdata_anomaly_detection_deepdive.ipynb Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> * address review comments * add ipynb files to dockerignore Co-authored-by: Tina Luedtke <kickoke@users.noreply.github.com> |
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| README.md | ||
Machine Learning Notebooks
This folder is a home for any documentation supporting machine learning related notebooks.
- Netdata anomaly detection deepdive: This is a starter notebook to help users understand how anomaly detection works in the Netdata agent and go a little deeper if they want.