[ad_1]
Synopsis
Learn to approach science as a method of finding the truth, rather than the truth itself, says Gu, 27, an MIT electrical engineering and computer science grad. Starting off by simply googling “epidemiology”, he went on to develop a highly successful Covid-19 model that combines machine learning with a classic infectious-disease simulator.
By Siobhan RobertsThe data scientist Youyang Gu thinks of himself as a realist—he declares it in his Twitter profile: “Presenter of unbiased takes. Realist.”When he noticed the scattershot covid-19 projections last spring—one model projected 2 million US deaths by the summer, another predicted 60,000—Gu questioned whether that was as good as the modeling could be. He decided to take a shot at making a covid-19 model himself. “My whole entire
- FONT SIZE
AbcSmall
AbcMedium
AbcLarge
Sign in to read the full article
You’ve got this Prime Story as a Free Gift
₹399/month
Monthly
PLAN
Billed Amount ₹399
₹208/month
(Save 49%)
Yearly
PLAN
Billed Amount ₹2,499
15
Days Trial
+Includes DocuBay and TimesPrime Membership.
₹150/month
(Save 63%)
2-Year
PLAN
Billed Amount ₹3,599
15
Days Trial
+Includes DocuBay and TimesPrime Membership.
Already a Member? Sign In now
Why ?
-
Sharp Insight-rich, Indepth stories across 20+ sectors
-
Access the exclusive Economic Times stories, Editorial and Expert opinion
-
Clean experience with
Minimal Ads -
Comment & Engage with ET Prime community -
Exclusive invites to Virtual Events with Industry Leaders -
A trusted team of Journalists & Analysts who can best filter signal from noise
[ad_2]
Source link