
When machine learning matters - a1k0n
https://erikbern.com/2016/08/05/when-machine-learning-matters.html
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thomasrossi
I think the interesting observation is: if you are using ML chances are 80% of
your algorithms are already published somewhere and available to all, so one
should tune in that 20% of his/her own field, some field which is not a common
research topic. I also think that a huge difference, once you have the same
algorithmic machine, is the quality of data you collect. That is also quite
differentiating, I mean, respect to your own business problem, gathering data
a way or the other may really destroy or boost your ML performances.

