diff --git a/sagemaker-python-sdk/1P_kmeans_highlevel/kmeans_mnist.ipynb b/sagemaker-python-sdk/1P_kmeans_highlevel/kmeans_mnist.ipynb
index 2f3ff60fa3..a3971c6bf2 100644
--- a/sagemaker-python-sdk/1P_kmeans_highlevel/kmeans_mnist.ipynb
+++ b/sagemaker-python-sdk/1P_kmeans_highlevel/kmeans_mnist.ipynb
@@ -59,20 +59,6 @@
     "bucket='<bucket-name>'"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data_key = 'kmeans_example/data'\n",
-    "data_location = 's3://{}/{}'.format(bucket, data_key)\n",
-    "output_location = 's3://{}/kmeans_example/output'.format(bucket)\n",
-    "\n",
-    "print('training data will be uploaded to: {}'.format(data_location))\n",
-    "print('training artifacts will be uploaded to: {}'.format(output_location))"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -149,6 +135,12 @@
    "source": [
     "from sagemaker import KMeans\n",
     "\n",
+    "data_location = 's3://{}/kmeans_highlevel_example/data'.format(bucket)\n",
+    "output_location = 's3://{}/kmeans_example/output'.format(bucket)\n",
+    "\n",
+    "print('training data will be uploaded to: {}'.format(data_location))\n",
+    "print('training artifacts will be uploaded to: {}'.format(output_location))\n",
+    "\n",
     "kmeans = KMeans(role=role,\n",
     "                train_instance_count=2,\n",
     "                train_instance_type='ml.c4.8xlarge',\n",
@@ -281,10 +273,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Uncomment and run to delete\n",
-    "\n",
-    "#import sagemaker\n",
-    "#sagemaker.Session().delete_endpoint(kmeans_predictor.endpoint)"
+    "import sagemaker\n",
+    "sagemaker.Session().delete_endpoint(kmeans_predictor.endpoint)"
    ]
   }
  ],
diff --git a/sagemaker-python-sdk/1P_kmeans_lowlevel/kmeans_mnist_lowlevel.ipynb b/sagemaker-python-sdk/1P_kmeans_lowlevel/kmeans_mnist_lowlevel.ipynb
index 68524bcd59..7d1b47a3b8 100644
--- a/sagemaker-python-sdk/1P_kmeans_lowlevel/kmeans_mnist_lowlevel.ipynb
+++ b/sagemaker-python-sdk/1P_kmeans_lowlevel/kmeans_mnist_lowlevel.ipynb
@@ -59,20 +59,6 @@
     "bucket='<bucket-name>'"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data_key = 'kmeans_example/data'\n",
-    "data_location = 's3://{}/{}'.format(bucket, data_key)\n",
-    "output_location = 's3://{}/kmeans_example/output'.format(bucket)\n",
-    "\n",
-    "print('training data will be uploaded to: {}'.format(data_location))\n",
-    "print('training artifacts will be uploaded to: {}'.format(output_location))"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -152,6 +138,10 @@
     "import io\n",
     "import boto3\n",
     "\n",
+    "data_key = 'kmeans_lowlevel_example/data'\n",
+    "data_location = 's3://{}/{}'.format(bucket, data_key)\n",
+    "print('training data will be uploaded to: {}'.format(data_location))\n",
+    "\n",
     "# Convert the training data into the format required by the SageMaker KMeans algorithm\n",
     "buf = io.BytesIO()\n",
     "write_numpy_to_dense_tensor(buf, train_set[0], train_set[1])\n",
@@ -190,6 +180,9 @@
     "          'eu-west-1': '438346466558.dkr.ecr.eu-west-1.amazonaws.com/kmeans:latest'}\n",
     "image = images[boto3.Session().region_name]\n",
     "\n",
+    "output_location = 's3://{}/kmeans_example/output'.format(bucket)\n",
+    "print('training artifacts will be uploaded to: {}'.format(output_location))\n",
+    "\n",
     "create_training_params = \\\n",
     "{\n",
     "    \"AlgorithmSpecification\": {\n",
@@ -473,9 +466,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Uncomment and run to delete\n",
-    "\n",
-    "# sagemaker.delete_endpoint(EndpointName=endpoint_name)"
+    "sagemaker.delete_endpoint(EndpointName=endpoint_name)"
    ]
   }
  ],