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#359: Lifecycle of a machine learning project

Talk Python To Me

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Milling Softer From the Outside End

Data scientists and machine learning engineers heavily leverage or aversion control, c i, cd, testing and in general, you know, clean code thas practices. A good bit of the hard datoday stuff for just following teones practices and really accelerate is to set those things up early on in the process of running a project. We could leave it all up to yhor if you were trying to debug something that's more clearly laid out than we were able to do with this interview. Dmetrius, go and jub i ith your thought than. Want to talk about a toll? Heroquie, oh, yes. I was just going to say that. One thing.

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