TDWI Anaheim Leadership Summit

Expert Session: When Models Go Rogue: Hard-Learned Lessons about Using Machine Learning in Production

August 7, 2018

David Talby, Ph.D.

CTO

Pacific AI

Much progress has been made over the past decade on process and tooling for managing large-scale, multitier, multicloud apps and APIs, but there is far less common knowledge on best practices for managing machine-learned models (classifiers, forecasters, etc.), especially once models are in production. Machine learning systems often fail in production in unexpected ways. This set of real-world case studies shows why this happens and explains what you can do about it, covering best practices and lessons learned from a decade of experience building and operating such systems at Fortune 500 companies. Topics include concept drift, selecting the right retrain pipeline, A/B testing challenges, offline vs. online measurement, adversarial learning systems, and their impact on project management.

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TDWI Anaheim Leadership Summit

Disneyland Hotel
Anaheim, CA
August 6–7

As to Disney properties/artwork: © Disney

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