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Shapley and Owen values for model output explainability: a hands-on case study

03/10/2023

Bridging the gap: Demystifying black-box algorithms with Mercury-explainability

21/09/2023

The Riddle of the Lancaster House: a hands-on exercise with Mercury-Reels

07/07/2023

Let the trees do the work: Hands-on optimal document search with Mercury-Settrie

19/06/2023

Mercury-Robust: ensuring the reliability of our ML models

24/05/2023

Mercury-Monitoring: analytical components for monitoring ML models

28/04/2023

Money talks: How AI models help us classify our expenses and income

26/01/2023

Mercury: Scaling Data Science reusability at BBVA

01/08/2022

How to tag data faster using Active Learning

01/10/2018

Self-Service Performance Tuning for Hive