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Machine learning workflows for developers

This repository has materials from a hands-on tutorial on machine learning workflows and using OpenShift for these. The goal of this workshop is to get application developers comfortable with some of the habits, concerns, and practices necessary to effectively incorporate machine learning workflows into their general engineering discipline. One notable aspect of the lab is that we offer students the opportunity to solve a real problem with machine learning in five fundamentally different ways -- and these approaches are quick enough to evaluate that attendees will be able to try out several and see which performs the best!

Our slides from presenting the lab at Red Hat Summit 2019 are available as a PDF or as a movie.

This repository is also intended to demonstrate the new reproducible workshops standards that are currently under development. We've intentionally let it fall short of the standard in places and have filed issues about these shortcomings. Feedback is welcome.

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This is material for a tutorial that @sophwats and @willb developed about machine learning workflows and about running them on OpenShift

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