(BA Math Berkeley) (MS Data Science Michigan) (Researcher in Mobile Health) (Former math teacher) (Fan of paragraphs)
Joined May 2014
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> favorite book: zero: the biography of a dangerous idea
Never heard this book brought up since. I bought this in Santa Barbara right before getting coffee with a girl (and her friends) I was in love with (obsessively infatuated with) who had no interest in me,
nearly half of you are new here
some things about me as we become friends:
> i’m in love with a girl named kate
> when 21, I made a pact to improve humanity
> was chronically depressed for 10+ yrs
> didn’t give up because I have 3 kids
> sold my company braintree venmo for $800m
> invested that into humanity
> crawled myself out of depression
> summited Kilimanjaro
> i fly airplanes
> favorite memory is telling my children bedtime stories
> have written three children books
> am learning to play the handpan
> favorite book: zero: the biography of a dangerous idea
> had toxic turf in backyard for years before realized it
i'll probably die in an ironic way... i hope you enjoy
I remember it argued that 0 as a mathematical concept came about in large part as a sort of natural post-hoc interpretation of the placeholder digit in Arabic numeral arithmetic;
Graduated with an MS in Data Science from Umich!
GPA, especially in grad school, really doesn't matter. But I got A, A, A+ in my last (and hardest) semester, for a final GPA of 3.886.
Today I started my work as a researcher at a lab and will hopefully publish interesting things this year. I never thought until very recently that I'd actually be a scientist!
Haven't read yet, but Bayesianism as a foundational language can basically express anything in statistics. Another example of this story (useful technique is special case of simple Bayesian setup) is Ridge Regression is a MAP of Bayesian regression with normal priors.
Things that work well are often optimal in some way. Bayesian updating fulfills some kind of universal property inside stochastic categories. I don't know the specifics, but there are "Markov categories" in the study of graphical models (diagrammatic Bayesian probability)