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Model Fairness Overview

In this module, we talk about the importance of trust and transparency in machine learning. Building and deploying models is just the start of our AI lifecycle, we need to ensure the models being deployed can be trusted, that they are reliable, that they are resilient, and that there is transparency in the outcomes. This lecture will focus on fairness in machine learning models and the use of the open source toolkit (AIF360) to address bias.


Scott D’Angelo

Developer Advocate

Scott D’Angelo is a Senior Software Engineer at IBM, where he focuses on delivering applications that showcase IBMs Cognitive, Data and Analytics portfolio. Previously, Scott was contributor to OpenStack, an open source project that provides Infrastructure-as-a-Service. He focused on its Block Storage service, code named Cinder, as a member of the Core Developer team.