Stas Don – Detecting Hidden Bias in Datasets Before Models Fail #bbuzz

More: https://2026.berlinbuzzwords.de/sessi... Speaker: Stas Don Hidden bias in datasets silently breaks machine learning systems in production. This talk shows how to detect data imbalance, leakage, and coverage gaps early using practical metrics, visualizations, and open-source tools—before misleading offline metrics turn into costly real-world failures. Machine learning models rarely fail because of algorithms — they fail because of data. This talk focuses on practical techniques for detecting hidden bias in datasets before models reach production. Drawing from real-world ML systems, it covers how regional, temporal, and behavioral imbalances distort model behavior while remaining invisible to standard metrics. Attendees will learn how to identify distribution drift, uncover feature leakage, and detect coverage gaps across segments and time windows. The session demonstrates concrete workflows, diagnostics, and visualizations that can be applied using open-source tools to improve data quality, model reliability, and long-term trust in ML-driven products. ### Follow us on Social Media and join the Community! Mastodon: https://floss.social/@berlinbuzzwords LinkedIn:   / berlin-buzzwords   Website: https://berlinbuzzwords.de Mail: [email protected] Berlin Buzzwords is an event by Plain Schwarz – https://plainschwarz.com