diff --git a/examples/sklearn-pipeline.ipynb b/examples/sklearn-pipeline.ipynb
index 0cbc5ee..ff7d1ee 100644
--- a/examples/sklearn-pipeline.ipynb
+++ b/examples/sklearn-pipeline.ipynb
@@ -7,8 +7,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#import pip\n",
-    "#pip.main(['install', 'skl2onnx', 'pydot', 'ebm2onnx', 'onnxruntime'])"
+    "import pip\n",
+    "pip.main(['install', 'skl2onnx', 'pydot', 'ebm2onnx', 'onnxruntime'])"
    ]
   },
   {
@@ -44,7 +44,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "55dc0909",
+   "id": "896e37d3",
    "metadata": {},
    "source": [
     "# Train a model with feature engineering\n",
@@ -111,7 +111,7 @@
     "        (\n",
     "            \"onehot\",\n",
     "            preprocessing.OneHotEncoder(\n",
-    "                sparse=True,\n",
+    "                sparse_output=True,\n",
     "                # Assumes I have 2 bool and 1 cat feature, and I'm specifying what\n",
     "                # values I want to drop when one hot encoding.\n",
     "                drop=list([0, 0, \"can_not_determine\"]),\n",
@@ -279,7 +279,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b9a44354",
+   "id": "62eb8ebd",
    "metadata": {},
    "source": [
     "# Convert the pipeline to ONNX\n",
@@ -337,7 +337,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22e0d3c6",
+   "id": "ff49e327",
    "metadata": {},
    "source": [
     "# Execute the pipeline with ONNX-Runtime"