The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 4 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Mike Driscoll: Solving real data problems beats taking data science courses
“I think that a lot of people who are interested in data science will, Decide that, you know, I gotta, I should go take a bunch of courses and read a bunch of books, and check a series of boxes, you know and I think that's actually the wrong approach. I think t…”
Mike Driscoll: Reject data science candidates who fail basic command-line tasks
“If someone can't get an answer to that, cannot pull that column off and turn it into a human readable date string, In the order of minutes, you do not want that person as a data scientist.”
Mike Driscoll: Hire ML talent for structured problems, domain experts otherwise
“If your data is already structured well enough, and you've got a set of criteria to define the success of your machine learning algorithm, then you should hire the strongest pure machine learner you can find. You should find someone who would, you know, who's …”
Mike Driscoll: Combining human data labeling with machine learning outperforms pure automation
“People make this sort of distinction of either it's machine learning or it's people. Either you've got a team in India or, you know, Romania working through the data, trying to make sense of it or you've got some algorithm working on it, but I think there is a…”