Is machine learning safe to use? text here: https://gist.github.com/anonymous/135f3b05b63dbd807ee6 …pic.twitter.com/IhaieMARl8
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@avibryant @b0rk interesting! is there EDA in machine learning?
@anyharder is that... something discriminant analysis? I don't know what that is
@b0rk @anyharder when I google I get exploratory data analysis? Which - I think so? But I may be missing some nuance of what's meant by that
@avibryant @b0rk @anyharder This is great! I'd add stress testing--simulating pessimistc data to assess consequences of model failure.
@avibryant @b0rk @anyharder This is easier in understandable models--since you can usually reason better about what will fool your model.
@avibryant interesting. I tend to think of (at least academic) ML one giant contribution to how we DO statistical inference @anyharder @b0rk
@avibryant i.e., papers tend to focus on methodology, algorithms, and less on asymptotics and proofs about inference. @anyharder @b0rk
@hausdorff_space @anyharder @b0rk the point I was trying to make is probably better expressed here: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.156.4933&rep=rep1&type=pdf …
@avibryant @anyharder @b0rk w/o buying into the hype, could concepts like deep learning ever have come out of the stats community?
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