diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb
index 2eb6265e2..7cd441267 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb
@@ -379,7 +379,7 @@
       "source": [
         "### Set up training parameters\n",
         "\n",
-        "This dictionary defines the AutoML and many models settings. For this forecasting task we need to define several settings inncluding the name of the time column, the maximum forecast horizon, and the partition column name definition.\n",
+        "This dictionary defines the AutoML and many models settings. For this forecasting task we need to define several settings including the name of the time column, the maximum forecast horizon, and the partition column name definition. We can also specify the number of n best runs to show in the UI, default is 1. \n",
         "\n",
         "| Property                           | Description|\n",
         "| :---------------                   | :------------------- |\n",
@@ -397,6 +397,7 @@
         "| **enable_engineered_explanations** | Engineered feature explanations will be downloaded if enable_engineered_explanations flag is set to True. By default it is set to False to save storage space. |\n",
         "| **time_series_id_column_names**     | The column names used to uniquely identify timeseries in data that has multiple rows with the same timestamp. |\n",
         "| **track_child_runs**               | Flag to disable tracking of child runs. Only best run is tracked if the flag is set to False (this includes the model and metrics of the run). |\n",
+        "| **n_best_runs**                    | Number of top n best runs |\n",
         "| **pipeline_fetch_max_batch_size**  | Determines how many pipelines (training algorithms) to fetch at a time for training, this helps reduce throttling when training at large scale. |\n",
         "| **partition_column_names**         | The names of columns used to group your models. For timeseries, the groups must not split up individual time-series. That is, each group must contain one or more whole time-series. |"
       ]
@@ -429,6 +430,7 @@
         "    \"forecast_horizon\": 6,\n",
         "    \"time_series_id_column_names\": partition_column_names,\n",
         "    \"track_child_runs\": False,\n",
+        "    \"n_best_runs\": 4,\n",
         "}\n",
         "\n",
         "mm_paramters = ManyModelsTrainParameters(\n",