Added an 'estimators' parameter

03_Run_Locally.ipynb

@@ -39,7 +39,7 @@
    "metadata": {},
    "source": [
     "## Azure subscription <a id='subscription'></a>\n",
-    "If you have multiple subscriptions select the subscription you want to use. You may supply either the subscription's name or the subscription's ID. If you want to run this in a different location that supports HyperDrive, you may enter the one you want to use. You can also set the name of the resource group in which this tutorial will add resources. *IMPORTANT NOTE:* The last notebook in this example will delete this resource group and all associated resources."
+    "If you have multiple subscriptions select the subscription you want to use. You may supply either the subscription's name or the subscription's ID. If you want to run this in a different location that supports HyperDrive, you may enter the one you want to use. You can also set the name of the resource group in which this tutorial will add resources. *IMPORTANT NOTE:* The last notebook in this example will delete this resource group and all associated resources. We also define the number of estimators to use for the local run."
    ]
   },
   {
@@ -55,7 +55,8 @@
     "subscription_name=\"YOUR_SUBSCRIPTION_NAME\"\n",
     "subscription_id=\"YOUR_SUBSCRIPTION_ID\"\n",
     "location=\"eastus\"\n",
-    "resource_group=\"hypetuning\""
+    "resource_group=\"hypetuning\"\n",
+    "estimators = 1000"
    ]
   },
   {
@@ -179,10 +180,10 @@
     "est = Estimator(source_directory=os.path.join('.', 'scripts'), \n",
     "                entry_script='TrainClassifier.py',\n",
     "                script_params={'--data-folder': os.path.abspath('.'),\n",
-    "                               '--estimators': '1000',\n",
-    "                               '--match': '5',\n",
-    "                               '--ngrams': '2',\n",
-    "                               '--min_child_samples': '10',\n",
+    "                               '--estimators': estimators,\n",
+    "                               '--match': 5,\n",
+    "                               '--ngrams': 2,\n",
+    "                               '--min_child_samples': 10,\n",
     "                               \"--save\": \"local_model\"},\n",
     "                compute_target='local',\n",
     "                conda_packages=['pandas==0.23.4',\n",