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Merge pull request #2456 from Blackmist/deprecation
adding missing deprecation note
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articles/machine-learning/concept-ml-pipelines.md

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:::moniker range="azureml-api-1"
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[!INCLUDE [dev v1](includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](./includes/machine-learning-cli-v1-deprecation.md)]
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:::moniker-end
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:::moniker range="azureml-api-2"
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[!INCLUDE [dev v2](includes/machine-learning-dev-v2.md)]

articles/machine-learning/how-to-network-security-overview.md

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:::moniker-end
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[!INCLUDE [dev v1](includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](./includes/machine-learning-cli-v1-deprecation.md)]
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:::moniker-end
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[!INCLUDE [managed-vnet-note](includes/managed-vnet-note.md)]

articles/machine-learning/how-to-troubleshoot-environments.md

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[!INCLUDE [dev v1](includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](./includes/machine-learning-cli-v1-deprecation.md)]
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In this article, learn how to troubleshoot common problems you may encounter with environment image builds and learn about AzureML environment vulnerabilities.

articles/machine-learning/v1/concept-azure-machine-learning-architecture.md

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[!INCLUDE [dev v1](../includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](../includes/machine-learning-cli-v1-deprecation.md)]
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This article applies to the first version (v1) of the Azure Machine Learning CLI & SDK. For version two (v2), see [How Azure Machine Learning works (v2)](../concept-azure-machine-learning-v2.md).
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Learn about the architecture and concepts for [Azure Machine Learning](../overview-what-is-azure-machine-learning.md). This article gives you a high-level understanding of the components and how they work together to assist in the process of building, deploying, and maintaining machine learning models.

articles/machine-learning/v1/concept-model-management-and-deployment.md

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[!INCLUDE [dev v1](../includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](../includes/machine-learning-cli-v1-deprecation.md)]
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In this article, learn how to apply machine learning operations (MLOps) practices in Azure Machine Learning to manage the lifecycle of your models. Machine learning operations practices can improve the quality and consistency of your machine learning solutions.
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> [!IMPORTANT]

articles/machine-learning/v1/how-to-configure-private-link.md

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[!INCLUDE [dev v1](../includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](../includes/machine-learning-cli-v1-deprecation.md)]
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In this document, you learn how to configure a private endpoint for your Azure Machine Learning workspace. For information on creating a virtual network for Azure Machine Learning, see [Virtual network isolation and privacy overview](../how-to-network-security-overview.md).
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articles/machine-learning/v1/introduction.md

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[!INCLUDE [dev v1](../includes/machine-learning-dev-v1.md)]
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[!INCLUDE [cli-version-info](../includes/machine-learning-cli-v1-deprecation.md)]
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All articles in this section document the use of the first version of Azure Machine Learning Python SDK (v1) or Azure CLI ml extension (v1). For information on the current SDK and CLI, see [Azure Machine Learning SDK and CLI v2](../concept-v2.md).
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