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PWL - QCon NYC Edition | John Langford on Making Contextual Decisions with Low Technical Debt

PWL - QCon NYC Edition | John Langford on Making Contextual Decisions with Low Technical Debt

About the show

Meetup: http://bit.ly/2uSFBlB
Slides: http://bit.ly/2f2Ycrl
Video: https://youtu.be/2bu3inBrZNg
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Sponsored by Two Sigma (@twosigma) and QCon NYC
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Description
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Applications and systems are constantly faced with decisions that require picking from a set of actions based on contextual information. Reinforcement-based learning algorithms such as contextual bandits can be very effective in these settings, but applying them in practice is fraught with technical debt, and no general system exists that supports them completely. We address this and create the first general system for contextual learning, called the Decision Service. Existing systems often suffer from technical debt that arises from issues like incorrect data collection and weak debuggability, issues we systematically address through...

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