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Analyzing & Preventing Unconscious Bias in Machine Learning
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| by Rachel Thomas Follow 0 Followers on Jun 12, 2018 |
38:12

Summary
Rachel Thomas keynotes on three case studies, attempting to diagnose bias, identify some sources, and discusses what it takes to avoid it.

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Bio

Rachel Thomas was selected by Forbes as one of “20 Incredible Women Advancing AI Research.” She is co-founder of fast.ai and a researcher-in-residence at the University of San Francisco Data Institute, where she teaches in the Masters in Data Science program. Her background includes energy trading, a data scientist + backend engineer at Uber, and a full-stack software instructor at Hackbright.

QCon.ai is a AI and Machine Learning conference held in San Francisco for developers, architects & technical managers focused on applied AI/ML.

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