Practical xAI: Building Trustworthy, Transparent & Unbiased ML Algorithms

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R&D Team

This talk was given at the Federated & Distributed Machine Learning Conference 2020 where we discuss the explore the growing influence and need of explainable AI in highly-regulated industries like healthcare, financial services and criminal justice system. 
We then discuss current techniques that are available for data scientists to assist them in explaining black-box AI models and end the talk with a real-world use case using an open-source python library, explainx, to build a narrative around xAI in production.

You can directly view the recorded talk here:

You can also access the slides used for this talk.

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