Testing ML systems - Changelog Master Feed

What this episode covers

Production ML systems include more than just the model. In these complicated systems, how do you ensure quality over time, especially when you are constantly updating your infrastructure, data and models? Tania Allard joins us to discuss the ins and outs of testing ML systems. Among other things, she presents a simple formula that helps you score your progress towards a robust system and identify problem areas.Featuring:Tania Allard – Website, GitHub, XChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes:“What’s your ML score” talk“Jupyter Notebooks: Friends or Foes?” talkJoel Grus’s episode: “AI code that facilitates good science”PapermillnbdevnbvalBooks“DevOps For Dummies” by Emily FreemanUpcoming Events: Register for upcoming webinars here!

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How long is this episode of Changelog Master Feed?

This episode is 47 minutes long.

When was this Changelog Master Feed episode published?

This episode was published on January 27, 2020.

What is this episode about?

Production ML systems include more than just the model. In these complicated systems, how do you ensure quality over time, especially when you are constantly updating your infrastructure, data and models? Tania Allard joins us to discuss the ins and...

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