"Machine Learning code generally doesn’t throw errors, it just underperforms" https://t.co/zIF0JhYb4j pic.twitter.com/zJIxPFxtJe
— Peter Skomoroch (@peteskomoroch) March 24, 2020
"Machine Learning code generally doesn’t throw errors, it just underperforms" https://t.co/zIF0JhYb4j pic.twitter.com/zJIxPFxtJe
— Peter Skomoroch (@peteskomoroch) March 24, 2020
The #coronavirus memes are getting scarily accurate... pic.twitter.com/8NbE5mZIcl
— Simon Kuestenmacher (@simongerman600) March 23, 2020
Ratcheting up surveillance to combat the pandemic now could permanently open the doors to more invasive forms of snooping later. It is a lesson Americans learned after the terrorist attacks of Sept. 11, 2001, civil liberties experts say.https://t.co/Stkn7vNrWE pic.twitter.com/hhyyGCW8j9
— Rachel Thomas (@math_rachel) March 23, 2020
Why is the AI Hype Absolutely Bonkers https://t.co/EambFHUP5C
— /MachineLearning (@slashML) March 23, 2020
Nice resource from the great @minebocek to aggregate #rstats analyses and representations of Covid-19 https://t.co/oj03udzHzv pic.twitter.com/OnibH4UR4B
— Michael Lopez (@StatsbyLopez) March 23, 2020
This is hilarious and also true: https://t.co/5ENcWBnZbY #DKE19
— Emily M. Bender (@emilymbender) March 22, 2020
China and South Korea both use mobile phone data to target interventions, but are invasive. This approach avoids the privacy invasion and may be more accurate.
— Chris Olah (@ch402) March 22, 2020
Not an expert, but this proposal for automatic contact tracing using “decentralized bluetooth proximity networks” seems like an elegant approach: https://t.co/A5JovYVi3c
— ch402 (@ch402) March 22, 2020
I'm still a fan of preprints, but I have to admit "The President could retweet a really shaky, non-randomized preprint" is a fairly solid argument pic.twitter.com/DRDhWDV4RW
— David Robinson (@drob) March 22, 2020
Kaggler @JohnMillerTX has helpful guidance, along with a template for creating analytics reports, for anyone looking to get started with our COVID-19 Open Research Dataset Challenge || https://t.co/t3jG1adfsc
— Kaggle (@kaggle) March 20, 2020
Another Bayesian model of coronavirus progression https://t.co/9JEvY1OfGm
— Andrew Gelman (@StatModeling) March 19, 2020
Bill Gates' 2015 TED talk "The next outbreak? We’re not ready" feels prescient https://t.co/QGc3eOFx4k ; a good "call to arms", reminder that so many of these🦠 are still with us https://t.co/0KYAMdn7br
— Andrej Karpathy (@karpathy) March 15, 2020