Refactor insurance notebook

python-client/docs/reference/notebooks/insurance_prediction_sklearn.ipynb → python-client/docs/reference/notebooks/insurance_prediction_lgbm.ipynb

@@ -3,7 +3,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "# Insurance charges prediction [LGBM]\n",
+    "# Insurance charges prediction [LightGBM]\n",
     "* Regression to predict the insurance charges based on medical and social data.\n",
     "* Dataset: <https://www.kaggle.com/datasets/teertha/ushealthinsurancedataset>\n",
     "\n",
@@ -27,7 +27,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "## Install the needed python packages"
+    "## Install necessary python packages"
    ],
    "metadata": {
     "collapsed": false
@@ -51,6 +51,18 @@
    },
    "id": "797dd8f836bd3a03"
   },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Troubleshooting\n",
+    "\n",
+    "If you encounter a segmentation fault on macOS at any point during this tutorial, check: https://docs.giskard.ai/en/latest/contribute/dev-environment.html"
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "e37ff3bea8055af3"
+  },
   {
    "cell_type": "markdown",
    "source": [
@@ -458,16 +470,17 @@
    "source": [
     "# Uploading the test suite will automatically save the model, dataset, tests, slicing & transformation functions inside the Giskard UI server\n",
     "# Create a Giskard client after having install the Giskard server (see documentation)\n",
-    "token = \"eyJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsInRva2VuX3R5cGUiOiJBUEkiLCJhdXRoIjoiUk9MRV9BRE1JTiIsImV4cCI6MTY5ODY3NzkwN30.J9BHtVtTGAugPExpUMUjoCHeR-Kh9hVHJ2S4Rac4ooc\"  # Find it in Settings in the Giskard server\n",
+    "token = \"API_TOKEN\"  # Find it in Settings in the Giskard server\n",
+    "\n",
     "client = GiskardClient(\n",
-    "    url=\"http://localhost:9000\",  # URL of your Giskard instance\n",
+    "    url=\"http://localhost:19000\",  # URL of your Giskard instance\n",
     "    token=token\n",
     ")\n",
     "\n",
-    "my_project = client.create_project(\"insurance_prediction\", \"insurance_prediction\", \"insurance_prediction\")\n",
+    "my_project = client.create_project(\"my_project\", \"PROJECT_NAME\", \"DESCRIPTION\")\n",
     "\n",
     "# Upload to the current project ✉️\n",
-    "test_suite.upload(client, \"insurance_prediction\")"
+    "test_suite.upload(client, \"my_project\")"
    ],
    "metadata": {
     "collapsed": false

python-client/docs/tutorials/data-types/tabular/index.md

@@ -41,6 +41,6 @@
 
 :::::{grid-item}
 :::{card} <h3><center>💸 Insurance charges prediction</center></h3>
-:link: ../../../reference/notebooks/insurance_prediction_sklearn.ipynb
+:link: ../../../reference/notebooks/insurance_prediction_lgbm.ipynb
 :::
 :::::

python-client/docs/tutorials/libraries/lightgbm/index.md

@@ -8,3 +8,9 @@
 :link: ../../../reference/notebooks/ieee_fraud_detection_adversarial_validation.ipynb
 :::
 :::::
+
+:::::{grid-item}
+:::{card} <h3><center>💸 Insurance charges prediction</center></h3>
+:link: ../../../reference/notebooks/insurance_prediction_lgbm.ipynb
+:::
+:::::

python-client/docs/tutorials/libraries/scikit-learn/index.md

@@ -45,8 +45,4 @@
 :::
 :::::
 
-:::::{grid-item}
-:::{card} <h3><center>💸 Insurance charges prediction</center></h3>
-:link: ../../../reference/notebooks/insurance_prediction_sklearn.ipynb
-:::
-:::::
+

python-client/docs/tutorials/tasks/regression/index.md

@@ -17,6 +17,6 @@
 
 :::::{grid-item}
 :::{card} <h3><center>💸 Insurance charges prediction</center></h3>
-:link: ../../../reference/notebooks/insurance_prediction_sklearn.ipynb
+:link: ../../../reference/notebooks/insurance_prediction_lgbm.ipynb
 :::
 :::::