Machine Learning Explainability: 'Do's' and 'Don'ts'
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Machine Learning Explainability: 'Do's' and 'Don'ts'

Keynote
Wednesday, November 25, 2020 13:30—13:50

Explaining the decision and behavior of machine learning models has become increasingly important, especially in industries such as finance, insurance and healthcare. But what does it mean to explain a model? When do we need to have that in place and when not? In this talk we will discuss such topics, and cover some requirements to make explainability successful in a complex organization.

Machine Learning Explainability: 'Do's' and 'Don'ts'
Presentation deck
Machine Learning Explainability: 'Do's' and 'Don'ts'
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Dr. Violeta Misheva
Dr. Violeta Misheva
ABN AMRO
Violeta is a data scientist, passionate about machine learning and topics such as fairness and explainability of machine learning models. She supplements her machine learning knowledge with her...
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