Research | Beyond explainability: A practical guide to managing risk in machine learning models
Beyond explainability: A practical guide to managing risk in machine learning models

Beyond explainability: A practical guide to managing risk in machine learning models

22 June 2018

This report offers a comprehensive guide for effectively managing risk in machine learning models. It presents a framework that enables data science and compliance teams to create better, more accurate, and more compliant models. The report stresses the importance of understanding the data used by models and implementing three lines of defence to assess and ensure their safety.

 

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