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I've adopted a similar attitude as you here when it comes to past machine learning jobs, and discussion of detail. What ends up being your bright shiny line that you don't cross? I tend to just not talk about the specific feature engineering, being relatively upfront about such basic things as "I used a random forest".



IMO, two things:

1) Features are everything 2) So is experience

When people buy machine learning experts they buy both of these things. Anyone can learn the math, it takes time to get good with it.




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