We often talk of the "state of #ML/#AI" as a way to refer to the health of the research community: how many interesting contributions have been made this year? Is progress slowing down? Are we running out of new ground-breaking paths to be explored?
This is not enough. [1/5]
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I have tried to make a point for versioning in ML projects: why we need it, what it provides us, what we are missing in terms of tools to do it properly. We need the equivalent of a
#StateOfDevOps report for#ML. [4/4]Show this thread -
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The blog post to go with the conference talk
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Writing about stuff to learn how it works, mostly in Rust.
Lead Engineer at