for me personally - the multiple times in my life when i have been in the process of putting someone in the ground - this kind of comment was right at the top of the list of the least helpful things people said.
i think that's true of almost all tech books in paper form
personally i think these work great because i can add cells to inspect data or try experiments easily as i'm reading to help me understand whats going on
One of the founders, Derek, is an interesting guy and built an impressive tech stack that drives the rooms with a very high degree of automation. I think most HN'ers would enjoy speaking with him about it.
his linkedin profile looks pretty legit to me.
http://www.linkedin.com/in/candel
I wouldn't want to get into a ML dick measuring contest with him anyway. H20 looks awesome too.
I think you are misinterpreting what he is saying about grid search. The grid search is just to narrow the field of parameters initially, he doesn't say how he would proceed after that point.
Just curious, what do you consider the state of the art? A Bayesian optimization? Wouldn't a grid search to start be like a uniform prior?
The rest of his suggestions looked on point to me, did you see anything else you would differ with? (i ask sincerely for my own education).
