Merge pull request #273913 from midesa/main

deprecation message for automl

Author: Stacyrch140

articles/synapse-analytics/machine-learning/tutorial-automl.md

@@ -1,6 +1,6 @@
 ---
-title: 'Tutorial: Train a model by using automated machine learning'
-description: Tutorial on how to train a machine learning model without code in Azure Synapse Analytics.
+title: 'Tutorial: Train a model by using automated machine learning (deprecated)'
+description: Tutorial on how to train a machine learning model without code in Azure Synapse Analytics (deprecated).
 ms.service: synapse-analytics 
 ms.subservice: machine-learning
 ms.topic: tutorial
@@ -10,7 +10,7 @@ author: midesa
 ms.author: midesa
 ---
 
-# Tutorial: Train a machine learning model without code
+# Tutorial: Train a machine learning model without code (deprecated)
 
 You can enrich your data in Spark tables with new machine learning models that you train by using [automated machine learning](../../machine-learning/concept-automated-ml.md). In Azure Synapse Analytics, you can select a Spark table in the workspace to use as a training dataset for building machine learning models, and you can do this in a code-free experience.
 

articles/synapse-analytics/spark/apache-spark-machine-learning-concept.md

@@ -36,7 +36,7 @@ Learn more about the machine learning capabilities by viewing the article on how
 ### SparkML and MLlib
 Spark's in-memory distributed computation capabilities make it a good choice for the iterative algorithms used in machine learning and graph computations. ```spark.ml``` provides a uniform set of high-level APIs that help users create and tune  machine learning pipelines.To learn more about ```spark.ml```, you can visit the [Apache Spark ML programming guide](https://spark.apache.org/docs/1.2.2/ml-guide.html).
 
-### Azure Machine Learning automated ML
+### Azure Machine Learning automated ML (deprecated)
 [Azure Machine Learning automated ML](../../machine-learning/concept-automated-ml.md) (automated machine learning) helps automate the process of developing machine learning models. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality. The components to run the Azure Machine Learning automated ML SDK is built directly into the Synapse Runtime.
 
 > [!WARNING]

articles/synapse-analytics/spark/apache-spark-machine-learning-training.md

@@ -37,7 +37,7 @@ The Microsoft Machine Learning library for Apache Spark is [MMLSpark](https://gi
 
 MMLSpark provides a layer on top of SparkML's low-level APIs when building scalable ML models, such as indexing strings, coercing data into a layout expected by machine learning algorithms, and assembling feature vectors. The MMLSpark library simplifies these and other common tasks for building models in PySpark.
 
-## Automated ML in Azure Machine Learning 
+## Automated ML in Azure Machine Learning (deprecated)
 Azure Machine Learning is a cloud-based environment that allows you to train, deploy, automate, manage, and track machine learning models. Automated ML in Azure Machine Learning accepts training data and configuration settings and automatically iterates through combinations of different feature normalization/standardization methods, models, and hyperparameter settings to arrive at the best model. 
 
 When using automated ML within Azure Synapse Analytics, you can leverage the deep integration between the different services to simplify authentication & model training. 

articles/synapse-analytics/toc.yml

@@ -1523,12 +1523,12 @@ items:
       - name: With Apache Spark MLlib
         displayName: train model
         href: ./spark/apache-spark-machine-learning-mllib-notebook.md
-      - name: With automated machine learning
+      - name: With automated machine learning (deprecated)
         items:
-        - name: Code-free
+        - name: Code-free (deprecated)
           displayName: train model, automated machine learning, automated ml, automl
           href: ./machine-learning/tutorial-automl.md
-        - name: In Python
+        - name: In Python (deprecated)
           displayName: train model, automated machine learning, automated ml, automl
           href: ./spark/apache-spark-azure-machine-learning-tutorial.md
       - name: With Horovod and Petastorm