U.S. Department of Energy

Pacific Northwest National Laboratory

Machine Learning Counterclockwise: Tips From the Trenches

Thursday, June 16, 2016
Mr. Shawn Rutledge
Principal Scientist
KFold Enterprises
"Ship early, ship often." Continuous integration. Test-driven development. As software engineering has matured in industry, these and other patterns/ anti-patterns have helped avoid the pitfalls common to moving from code to working software systems. As machine learning grows in practice and pervasiveness in industry, similar patterns can help the move from models into working machine learning pipelines and systems. I'll propose some of these patterns and relate tips and best practices from an industry practitioner's perspective. Along the way I hope to challenge researchers working in the area of machine learning with open problems in feature representations, model deployments, and model explanation.
Speaker Bio

Mr. Rutledge is an accomplished machine learning practitioner with over a decade of experience building analytics solutions across verticals as diverse as financial services, travel, and social media. He is currently Principal Scientist at kFold Enterprises, a machine learning products and services firm he founded in 2009. While he has served as a technology executive for IBM, First Data, and Expedia, he is most at home in the startup environment and has been a principal contributor, leader, advisor, and angel investor to more than a dozen Seattle area startups. Shawn holds a bachelors degree in Computer Science and has completed graduate coursework in Statistics at Stanford.

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