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

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ms.subservice: machine-learning
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ms.topic: tutorial
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ms.reviewer: sngun, garye
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ms.date: 09/03/2021
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author: nelgson
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ms.author: negust
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ms.date: 03/06/2024
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author: midesa
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ms.author: midesa
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---
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# Tutorial: Train a machine learning model without code
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If you don't have an Azure subscription, [create a free account before you begin](https://azure.microsoft.com/free/).
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> [!WARNING]
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> - Effective September 29, 2023, Azure Synapse will discontinue official support for [Spark 2.4 Runtimes](../spark/apache-spark-24-runtime.md). Post September 29, 2023, we will not be addressing any support tickets related to Spark 2.4. There will be no release pipeline in place for bug or security fixes for Spark 2.4. Utilizing Spark 2.4 post the support cutoff date is undertaken at one's own risk. We strongly discourage its continued use due to potential security and functionality concerns.
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> - As part of the deprecation process for Apache Spark 2.4, we would like to notify you that AutoML in Azure Synapse Analytics will also be deprecated. This includes both the low code interface and the APIs used to create AutoML trials through code.
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> - Please note that AutoML functionality was exclusively available through the Spark 2.4 runtime.
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> - For customers who wish to continue leveraging AutoML capabilities, we recommend saving your data into your Azure Data Lake Storage Gen2 (ADLSg2) account. From there, you can seamlessly access the AutoML experience through Azure Machine Learning (AzureML). Further information regarding this workaround is available [here](../machine-learning/access-data-from-aml.md).
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## Prerequisites
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- An [Azure Synapse Analytics workspace](../get-started-create-workspace.md). Ensure that it has an Azure Data Lake Storage Gen2 storage account configured as the default storage. For the Data Lake Storage Gen2 file system that you work with, ensure that you're the *Storage Blob Data Contributor*.

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