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Update tutorial-network-isolation-for-feature-store.md
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articles/machine-learning/tutorial-network-isolation-for-feature-store.md

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# Tutorial 6: Network isolation with feature store
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[!INCLUDE [preview disclaimer](includes/machine-learning-preview-generic-disclaimer.md)]
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An Azure Machine Learning managed feature store lets you discover, create, and operationalize features. Features serve as the connective tissue in the machine learning lifecycle, starting from the prototyping phase, where you experiment with various features. That lifecycle continues to the operationalization phase, where you deploy your models, and inference steps look up the feature data. For more information about feature stores, read the [feature store concepts](./concept-what-is-managed-feature-store.md) document.
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This tutorial describes how to configure secure ingress through a private endpoint, and secure egress through a managed virtual network.
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## Next steps
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* [Part 2: Experiment and train models using features](./tutorial-experiment-train-models-using-features.md)
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* [Part 3: Enable recurrent materialization and run batch inference](./tutorial-enable-recurrent-materialization-run-batch-inference.md)
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* [Part 3: Enable recurrent materialization and run batch inference](./tutorial-enable-recurrent-materialization-run-batch-inference.md)

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