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chore: Merge branch 'main' into chore/bump-helm-charts-pre-25.7.0
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docs/modules/demos/pages/jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data.adoc

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@@ -123,8 +123,6 @@ Click on the double arrow (⏩️) to execute the Python scripts (click on the i
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image::jupyterhub-pyspark-hdfs-anomaly-detection-taxi-data/jupyter_hub_run_notebook.png[link=https://github.com/stackabletech/demos/blob/main/stacks/jupyterhub-pyspark-hdfs/notebook.ipynb,window=_blank]
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You can also inspect the `hdfs` folder where the `core-site.xml` and `hdfs-site.xml` from the discovery ConfigMap of the HDFS cluster are located.
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The Python notebook uses libraries such as `pandas` and `scikit-learn` to analyze the data.
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In addition, since the model training is delegated to a Spark Connect server, some of these dependencies, most notably `scikit-learn`, must also be made available on the Spark Connect pods.
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For convenience, a custom image is used in this demo that bundles all the required libraries for both the notebook and the Spark Connect server.

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