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ML is a relatively young field, and decades behind Software Engineering in terms of best practices for running production systems. CI/CD massively improved the innovation cycle time and quality of production software, and I believe it is key for building robust production ML systems as well. CML looks like a really easy to use product for bringing CI/CD to ML projects.

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Just something I wanted to share which might be of interest on this side of things.

The CD Foundation has a SIG around MLOps which is pretty active and has some awesome folk participating.

For anyone who's interested in this space, there's some more detail here: https://cd.foundation/blog/2020/02/11/announcing-the-cd-foun...

Thanks for the kind words! DevOps has had profound results and we think culturally and technically, it's the right moment to push for those practices in ML.

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