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    <title>topic Responsible AI on Databricks in Machine Learning</title>
    <link>https://community.databricks.com/t5/machine-learning/responsible-ai-on-databricks/m-p/31315#M1672</link>
    <description>&lt;P&gt;&lt;B&gt;Looking to learn how you can use responsible AI toolkits on Databricks? Interested in learning how you can incorporate open source tools like SHAP and Fairlearn with Databricks?&lt;/B&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would recommend checking out this blog: &lt;A href="https://www.databricks.com/blog/2022/09/16/mitigating-bias-machine-learning-shap-and-fairlearn.html?_ga=2.117664137.166158936.1663532943-1468227001.1645719051" alt="https://www.databricks.com/blog/2022/09/16/mitigating-bias-machine-learning-shap-and-fairlearn.html?_ga=2.117664137.166158936.1663532943-1468227001.1645719051" target="_blank"&gt;&lt;U&gt;Mitigating Bias in Machine Learning With SHAP and Fairlearn&lt;/U&gt;&lt;/A&gt; from my colleague @Sean Owen​. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;SHAP is a explainability framework used to determine the relative importance of features used in an ML model to give better transparency, especially when used with more complex models. Fairlearn is a framework to quantify and minimize bias inherit to datasets used an in ML model.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;In addition to leveraging these frameworks as discussed in the article, out of the box Databricks automatically logs SHAP explainability plots with most ml frameworks using &lt;A href="https://www.mlflow.org/docs/latest/models.html#model-evaluation" alt="https://www.mlflow.org/docs/latest/models.html#model-evaluation" target="_blank"&gt;&lt;U&gt;mlflow autolog&lt;/U&gt;&lt;/A&gt; and SHAP plots are automatically generated as part of &lt;A href="https://docs.databricks.com/applications/machine-learning/automl.html" alt="https://docs.databricks.com/applications/machine-learning/automl.html" target="_blank"&gt;&lt;U&gt;Databricks AutoML&lt;/U&gt;&lt;/A&gt; notebook output. You can learn more at our &lt;A href="https://www.databricks.com/explainable-ai" alt="https://www.databricks.com/explainable-ai" target="_blank"&gt;&lt;U&gt;Explainable AI home page&lt;/U&gt;&lt;/A&gt;.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Let us know how you plan to add Responsible AI frameworks to your ML workflows in the chat!&lt;/P&gt;</description>
    <pubDate>Tue, 20 Sep 2022 08:12:19 GMT</pubDate>
    <dc:creator>isaac_gritz</dc:creator>
    <dc:date>2022-09-20T08:12:19Z</dc:date>
    <item>
      <title>Responsible AI on Databricks</title>
      <link>https://community.databricks.com/t5/machine-learning/responsible-ai-on-databricks/m-p/31315#M1672</link>
      <description>&lt;P&gt;&lt;B&gt;Looking to learn how you can use responsible AI toolkits on Databricks? Interested in learning how you can incorporate open source tools like SHAP and Fairlearn with Databricks?&lt;/B&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I would recommend checking out this blog: &lt;A href="https://www.databricks.com/blog/2022/09/16/mitigating-bias-machine-learning-shap-and-fairlearn.html?_ga=2.117664137.166158936.1663532943-1468227001.1645719051" alt="https://www.databricks.com/blog/2022/09/16/mitigating-bias-machine-learning-shap-and-fairlearn.html?_ga=2.117664137.166158936.1663532943-1468227001.1645719051" target="_blank"&gt;&lt;U&gt;Mitigating Bias in Machine Learning With SHAP and Fairlearn&lt;/U&gt;&lt;/A&gt; from my colleague @Sean Owen​. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;SHAP is a explainability framework used to determine the relative importance of features used in an ML model to give better transparency, especially when used with more complex models. Fairlearn is a framework to quantify and minimize bias inherit to datasets used an in ML model.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;In addition to leveraging these frameworks as discussed in the article, out of the box Databricks automatically logs SHAP explainability plots with most ml frameworks using &lt;A href="https://www.mlflow.org/docs/latest/models.html#model-evaluation" alt="https://www.mlflow.org/docs/latest/models.html#model-evaluation" target="_blank"&gt;&lt;U&gt;mlflow autolog&lt;/U&gt;&lt;/A&gt; and SHAP plots are automatically generated as part of &lt;A href="https://docs.databricks.com/applications/machine-learning/automl.html" alt="https://docs.databricks.com/applications/machine-learning/automl.html" target="_blank"&gt;&lt;U&gt;Databricks AutoML&lt;/U&gt;&lt;/A&gt; notebook output. You can learn more at our &lt;A href="https://www.databricks.com/explainable-ai" alt="https://www.databricks.com/explainable-ai" target="_blank"&gt;&lt;U&gt;Explainable AI home page&lt;/U&gt;&lt;/A&gt;.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Let us know how you plan to add Responsible AI frameworks to your ML workflows in the chat!&lt;/P&gt;</description>
      <pubDate>Tue, 20 Sep 2022 08:12:19 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/responsible-ai-on-databricks/m-p/31315#M1672</guid>
      <dc:creator>isaac_gritz</dc:creator>
      <dc:date>2022-09-20T08:12:19Z</dc:date>
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