From 3eca92f90b5ef0d3864229d9d709b5849dbd81af Mon Sep 17 00:00:00 2001
From: Chuan Tian <77308530+ctian-msft@users.noreply.github.com>
Date: Mon, 4 Apr 2022 15:24:46 -0700
Subject: [PATCH] Update auto-ml-forecasting-orange-juice-sales.ipynb

---
 .../auto-ml-forecasting-orange-juice-sales.ipynb       | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb
index a25344f68..a95a32dbe 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb
@@ -468,6 +468,14 @@
         "remote_run.wait_for_completion()"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "#### Many Models Option\n",
+        "In this data set, we have more than one time series in the data set (for each brand in each store), and the above steps trained the same models for all the series. If training each model for each series makes more sense to you, we recommend you to consider many models accelerator which allows user to train and manage millions of models in parallel. Please refer to [this notebook](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb) for more details."
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},
@@ -841,4 +849,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 4
-}
\ No newline at end of file
+}