Have been following these guys for a while and had a lot of fun playing with their API when they were still in the alpha stage. Really impressive stuff being able to do NLP in a black-box fashion. I'm sure it took a lot of time getting the default machine learning params to work well in so many cases. Admittedly haven't tried any competitor's products yet so would be keen to hear from those who have how it compares.
but really - and I'm sure this is your `secret sauce' so you don't want to give away too much - how do you get hypers which just work out the box? was this some kind of meta-regression on the hypers? Or did you do a bayesian optimisation?
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[ 2.7 ms ] story [ 38.7 ms ] threadIs that a typo?