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Remove ms.subservice = rai paired with ms.service = machine-learning. Replaced by ms.subservice = responsible-ai paired with ms.service = azure-machine-learning
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articles/machine-learning/concept-causal-inference.md

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@@ -3,8 +3,8 @@ title: Make data-driven policies and influence decision-making
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titleSuffix: Azure Machine Learning
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description: Make data-driven decisions and policies with the Responsible AI dashboard's integration of the causal analysis tool EconML.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: how-to
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-counterfactual-analysis.md

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@@ -3,8 +3,8 @@ title: Counterfactuals analysis and what-if
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titleSuffix: Azure Machine Learning
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description: Generate diverse counterfactual examples with feature perturbations to see minimal changes required to achieve desired prediction with the Responsible AI dashboard's integration of DiCE machine learning.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: how-to
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-data-analysis.md

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titleSuffix: Azure Machine Learning
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description: Perform exploratory data analysis to understand feature biases and imbalances by using the Responsible AI dashboard's data analysis.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: how-to
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-error-analysis.md

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@@ -3,8 +3,8 @@ title: Assess errors in machine learning models
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titleSuffix: Azure Machine Learning
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description: Assess model error distributions in different cohorts of your dataset with the Responsible AI dashboard's integration of error analysis.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: how-to
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-fairness-ml.md

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titleSuffix: Azure Machine Learning
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description: Learn about machine learning fairness and how the Fairlearn Python package can help you assess and mitigate unfairness.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: conceptual
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-responsible-ai-dashboard.md

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@@ -3,8 +3,8 @@ title: Assess AI systems and make data-driven decisions with Azure Machine Learn
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titleSuffix: Azure Machine Learning
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description: Learn how to use the comprehensive UI and SDK/YAML components in the Responsible AI dashboard to debug your machine learning models and make data-driven decisions.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: how-to
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-responsible-ai-scorecard.md

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@@ -3,8 +3,8 @@ title: Share Responsible AI insights and make data-driven decisions with Azure M
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titleSuffix: Azure Machine Learning
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description: Learn about how to use the Responsible AI scorecard to share responsible AI insights from your machine learning models and make data-driven decisions with non-technical and technical stakeholders.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: conceptual
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-responsible-ai.md

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titleSuffix: Azure Machine Learning
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description: Learn what Responsible AI is and how to use it with Azure Machine Learning to understand models, protect data, and control the model lifecycle.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: conceptual
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ms.author: lagayhar
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author: lgayhardt

articles/machine-learning/concept-sourcing-human-data.md

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description: Learn best practices for mitigating potential harm to people—especially in vulnerable groups—and building balanced datasets when collecting human data manually.
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author: lgayhardt
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ms.author: lagayhar
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.reviewer: nhudo
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ms.topic: conceptual
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ms.date: 12/30/2023

articles/machine-learning/how-to-responsible-ai-dashboard.md

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@@ -3,8 +3,8 @@ title: Use the Responsible AI dashboard in Azure Machine Learning studio
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titleSuffix: Azure Machine Learning
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description: Learn how to use the various tools and visualization charts in the Responsible AI dashboard in Azure Machine Learning.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: rai
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ms.service: azure-machine-learning
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ms.subservice: responsible-ai
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ms.topic: how-to
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ms.reviewer: None
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ms.author: lagayhar

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