Merge pull request #189305 from xiaoharper/harper-mlclassic

update migration article

Author: hmacgregor1

articles/machine-learning/media/migrate-rebuild-experiment/save-model.png

@@ -24,6 +24,8 @@ Learn how to migrate from Studio (classic) to Azure Machine Learning. Azure Mach
 
 This is a guide for a basic "lift and shift" migration. If you want to optimize an existing machine learning workflow, or modernize a machine learning platform, see the [Azure Machine Learning adoption framework](https://aka.ms/mlstudio-classic-migration-repo) for additional resources including digital survey tools, worksheets, and planning templates.
 
+Please work with your Cloud Solution Architect on the migration. 
+
 ![Azure ML adoption framework](./media/migrate-overview/aml-adoption-framework.png)
 
 ## Recommended approach
@@ -59,6 +61,8 @@ To migrate to Azure Machine Learning, we recommend the following approach:
 1. Align an actionable Azure Machine Learning adoption plan to business outcomes.
 1. Prepare people, processes, and environments for change.
 
+Please work with your Cloud Solution Architect to define your strategy. 
+
 See the [Azure Machine Learning Adoption Framework](https://aka.ms/mlstudio-classic-migration-repo) for planning resources including a planning doc template. 
 
 ## Step 3: Rebuild your first model

articles/machine-learning/media/migrate-rebuild-experiment/search-model-in-list.png

@@ -83,7 +83,20 @@ After the run finishes, you can check the results of each module:
     - **View Log**: View driver and system logs. Use the **70_driver_log** to see information related to your user-submitted script such as errors and exceptions.
 
 > [!IMPORTANT]
-> Designer components use open source Python packages, compared to C# packages in Studio (classic). As a result, module output may vary slightly between the designer and Studio (classic). 
+> Designer components use open source Python packages to implement machine learning algorithms. However Studio (classic) uses a Microsoft internal C# library. Therefore, prediction result may vary between the designer and Studio (classic). 
+
+
+## Save trained model to use in another pipeline
+
+Sometimes you may want to save the model trained in a pipeline and use the model in another pipeline later. In Studio (classic), all trained models are saved in "Trained Models" category in the module list. In designer, the trained models are automatically registered as file dataset with a system generated name. Naming convention follows "MD - pipeline draft name - component name - Trained model ID" pattern. 
+
+To give a trained model a meaningful name, you can register the output of **Train Model** component as a **file dataset**. Give it the name you want, for example linear-regression-model. 
+
+![Screenshot showing how to save trained model.](./media/migrate-rebuild-experiment/save-model.png)
+
+You can find the trained model in "Dataset" category in the component list or search it by name. Then connect the trained model to a **Score Model** component to use it for prediction. 
+
+![Screenshot showing how to find trained model.](./media/migrate-rebuild-experiment/search-model-in-list.png)
 
 
 ## Next steps

articles/machine-learning/migrate-overview.md

@@ -12,7 +12,7 @@ ms.author: cgronlun
 > [!IMPORTANT]
 > Support for Machine Learning Studio (classic) will end on 31 August 2024. We recommend you transition to [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/) by that date.
 >
-> Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources.  
+> Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources (workspace and web service plan). Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) experiments and web services.  
 > 
 > -	See [information on moving machine learning projects from ML Studio (classic) to Azure Machine Learning](../articles/machine-learning/migrate-overview.md). 
 > -	Learn more about [Azure Machine Learning](../articles/machine-learning/overview-what-is-azure-machine-learning.md)