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articles/machine-learning/how-to-machine-learning-interpretability-aml.md

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@@ -365,7 +365,8 @@ Follow one of these paths to access the explanations dashboard in Azure Machine
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[![Visualization Dashboard with Aggregate Feature Importance in AzureML studio in experiments](./media/how-to-machine-learning-interpretability-aml/model-explanation-dashboard-aml-studio.png)](./media/how-to-machine-learning-interpretability-aml/model-explanation-dashboard-aml-studio.png#lightbox)
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* **Models** pane
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1. If you registered your original model by following the steps in [Deploy models with Azure Machine Learning](v1/how-to-deploy-and-where.md), you can select **Models** in the left pane to view it.
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1. If you registered your original model by following the steps in [Deploy models with Azure Machine Learning](./how-to-deploy-managed-online-endpoints.md), you can select **Models** in the left pane to view it.
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1. Select a model, and then the **Explanations** tab to view the explanations dashboard.
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## Interpretability at inference time
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1. Deploy the image to a compute target, by following these steps:
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1. If needed, register your original prediction model by following the steps in [Deploy models with Azure Machine Learning](v1/how-to-deploy-and-where.md).
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1. If needed, register your original prediction model by following the steps in [Deploy models with Azure Machine Learning](./how-to-deploy-managed-online-endpoints.md).
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1. Create a scoring file.
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