Separate cluster creation from training in Optuna example

optuna-xgboost/optuna-xgboost.ipynb

@@ -68,25 +68,49 @@
     "    return accuracy"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Connect to Coiled"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from dask.distributed import Client\n",
     "import coiled\n",
-    "import optuna\n",
-    "import dask_optuna\n",
-    "import joblib\n",
+    "from dask.distributed import Client\n",
     "\n",
-    "# Create a Dask cluster with Coiled\n",
-    "cluster = coiled.Cluster(n_workers=10, software=\"jrbourbeau/optuna\")\n",
-    "# Connect Dask to our cluster\n",
+    "cluster = coiled.Cluster(\n",
+    "    n_workers=10, \n",
+    "    software=\"jrbourbeau/optuna\"\n",
+    ")\n",
     "client = Client(cluster)\n",
-    "print(f\"Dask dashboard is available at {client.dashboard_link}\")\n",
     "client.wait_for_workers(10)\n",
     "\n",
+    "client"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Train with Optuna"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import optuna\n",
+    "import dask_optuna\n",
+    "import joblib\n",
+    "\n",
     "# Create Dask-compatible Optuna storage class\n",
     "storage = dask_optuna.DaskStorage()\n",
     "\n",