Open Source Summit ELC Europe 2019: Explaining the Black Box of Machine Lear...

Being able to reason about the predictions of a machine learning system is becoming increasingly important as sophisticated, non-linear predictive models are being adopted across the enterprise and beyond. In this talk we will discuss some requirements and challenges of model explanation algorithms and demo some practical examples using the open-source library Alibi we've developed at Seldon. - What makes an explanation interpretable? - The trade-off between interpretability and fidelity of an explanation algorithm - Practical examples of using some interpretable techniques (e.g.