To this day when I see the runif() function I first read it as "run if" and not "r unif". #rstats
— Sharon Machlis (@sharon000) July 10, 2018
To this day when I see the runif() function I first read it as "run if" and not "r unif". #rstats
— Sharon Machlis (@sharon000) July 10, 2018
Here’s what @dpatil has been hinting at: Doing Good Data Science—first of a series on data science and ethics. By DJ, @hmason, & @mikeloukides https://t.co/jNQOiQ0X4t
— Mike Loukides (@mikeloukides) July 10, 2018
"We need to stop teaching abstinence-only statistics, telling students they can only do it if they are in a committed relationship with a statistician. But all their friends are out there doing statistics and having a great time.
— Kelly Bodwin (@KellyBodwin) July 10, 2018
We need to teach safe stats."
- @hadleywickham
One of the more striking examples I've seen of an algorithm solving the wrong problem pic.twitter.com/tMVpC54RlJ
— Janelle Shane (@JanelleCShane) July 9, 2018
Generally fun and the first table seems like a good reminder that the minimizer of L2 approximation is usually not also the L∞ minimizer: https://t.co/ohjvusrMDG
— John Myles White (@johnmyleswhite) July 9, 2018
To develop expertise in AI, you can’t just read papers; you have to read other people’s code. And you can’t just read it, you have to re-implement it. Part of your understanding is gained only through the practice of coding itself.
— hardmaru (@hardmaru) July 9, 2018
Architects build models from cardboard; AI researchers build them from code. These prototypes are not engineering models, subjected to serious real-world testing. They’re just “sketches” to give a sense of how something might work.
— hardmaru (@hardmaru) July 9, 2018
“The actual practice of AI research is more like architectural design than like electrical engineering.” https://t.co/1QQV8c3rmg
— hardmaru (@hardmaru) July 9, 2018
4/4
— Judea Pearl (@yudapearl) July 8, 2018
for discussion topics that have been ignored or suppressed by
mainstream literature and, simultaneously,
try to be as flexible, honest and open-minded
as I can in responding to your questions and comments.
Unortunately, I can only Tweet once or twice
a day. #bookofwhy
3/4
— Judea Pearl (@yudapearl) July 8, 2018
My goal was and is: the democratization of causal
inference . By that I mean empowering
students and researchers to understand causal inference
on their own, without waiting for professors or
journal editors to catch up.
Toward that end, I will continue to bring up ...
2/4
— Judea Pearl (@yudapearl) July 8, 2018
First, I find the intellectual exercise of
compacting pages of technical analysis into
3-4 sentences challenging, educational and empowering.
Second, the genuine quest for understanding I
see among you gives me the hope that my primary goal
of writing the Book is realizable.
1/4
— Judea Pearl (@yudapearl) July 8, 2018
10 days ago, when I decided to go on Twitter,
I did not know what I am getting into. Today,
with over 5,000 followers, I feel a sense of
obligation to give you a progress report, and to
reflect on this experience. This will probably take
4 Tweets - stay tuned #bookofwhy