diff --git a/tutorials/img-classification-part2-deploy.ipynb b/tutorials/img-classification-part2-deploy.ipynb
index 7034a510..65537187 100644
--- a/tutorials/img-classification-part2-deploy.ipynb
+++ b/tutorials/img-classification-part2-deploy.ipynb
@@ -581,7 +581,7 @@
     "> * Deploy the model to ACI\n",
     "> * Test the deployed model\n",
     " \n",
-    "You can also try out the [Automatic algorithm selection tutorial](03.auto-train-models.ipynb) to see how Azure Machine Learning can auto-select and tune the best algorithm for your model and build that model for you."
+    "You can also try out the [regression tutorial](regression-part1-data-prep.ipynb)."
    ]
   }
  ],
diff --git a/tutorials/regression-part2-automated-ml.ipynb b/tutorials/regression-part2-automated-ml.ipynb
index fba01af8..b9504783 100644
--- a/tutorials/regression-part2-automated-ml.ipynb
+++ b/tutorials/regression-part2-automated-ml.ipynb
@@ -55,8 +55,6 @@
     "import azureml.core\n",
     "import pandas as pd\n",
     "from azureml.core.workspace import Workspace\n",
-    "from azureml.train.automl.run import AutoMLRun\n",
-    "import time\n",
     "import logging"
    ]
   },
@@ -93,7 +91,8 @@
     "output['Location'] = ws.location\n",
     "output['Project Directory'] = project_folder\n",
     "pd.set_option('display.max_colwidth', -1)\n",
-    "pd.DataFrame(data=output, index=['']).T"
+    "outputDf = pd.DataFrame(data = output, index = [''])\n",
+    "outputDf.T"
    ]
   },
   {
@@ -112,7 +111,6 @@
    "outputs": [],
    "source": [
     "import azureml.dataprep as dprep\n",
-    "import os\n",
     "\n",
     "file_path = os.path.join(os.getcwd(), \"dflows.dprep\")\n",
     "\n",
@@ -308,7 +306,6 @@
     "    metrics = {k: v for k, v in run.get_metrics().items() if isinstance(v, float)}\n",
     "    metricslist[int(properties['iteration'])] = metrics\n",
     "\n",
-    "import pandas as pd\n",
     "rundata = pd.DataFrame(metricslist).sort_index(1)\n",
     "rundata"
    ]
@@ -351,7 +348,7 @@
     "description = 'Automated Machine Learning Model'\n",
     "tags = None\n",
     "local_run.register_model(description=description, tags=tags)\n",
-    "local_run.model_id # Use this id to deploy the model as a web service in Azure"
+    "print(local_run.model_id) # Use this id to deploy the model as a web service in Azure"
    ]
   },
   {
@@ -471,7 +468,7 @@
     "> * Explored and reviewed training results\n",
     "> * Registered the best model\n",
     "\n",
-    "[Deploy your model](02.deploy-models.ipynb) with Azure Machine Learning."
+    "You can also try out the [image classification tutorial](img-classification-part1-training.ipynb)."
    ]
   }
  ],