update notebook and zip file so notebook runs

bring-custom-container.ipynb

@@ -339,6 +339,13 @@
     "The API calls the Amazon SageMaker `CreateTrainingJob` API to start model training. The API uses configuration you provided to create the `estimator` and the specified input training data to send the `CreatingTrainingJob` request to Amazon SageMaker."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -358,10 +365,21 @@
     "                                output_path=\"s3://{}/output\".format(sess.default_bucket()),\n",
     "                                sagemaker_session=sess)\n",
     "\n",
-    "file_location = data_location + '/iris.csv'\n",
+    "file_location = data_location + '/train.csv'\n",
     "tree.fit(file_location)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "file_location"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -514,9 +532,9 @@
  "metadata": {
   "instance_type": "ml.t3.medium",
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (Data Science)",
    "language": "python",
-   "name": "python3"
+   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/datascience-1.0"
   },
   "language_info": {
    "codemirror_mode": {
@@ -528,7 +546,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.7.10"
   }
  },
  "nbformat": 4,