Andrew Fairless – Page 71 – Andrew Fairless, Ph.D.

What I Read: Dynamic Data Testing

By Andrew Fairless on February 16, 2021January 18, 2021

https://medium.com/anomalo-hq/dynamic-data-testing-f831435dba90 Dynamic Data TestingJeremy StanleyNov 18 “Can’t we write down a clear set of rules that govern exactly how our data should behave, just like we do when testing software?Continue readingWhat I Read: Dynamic Data Testing

What I Read: Revisiting Sutton’s Bitter Lesson for AI

By Andrew Fairless on February 15, 2021January 18, 2021

https://blog.exxactcorp.com/compute-goes-brrr-revisiting-suttons-bitter-lesson-artificial-intelligence/ Deep LearningCompute Goes Brrr: Revisiting Sutton’s Bitter Lesson for Artificial IntelligenceMarketing, October 27, 2020 “The main driver of AI progress, according to Sutton, is the increasing availability of computeContinue readingWhat I Read: Revisiting Sutton’s Bitter Lesson for AI

What I Read: The way we train AI is flawed

By Andrew Fairless on February 15, 2021January 18, 2021

https://www.technologyreview.com/2020/11/18/1012234/training-machine-learning-broken-real-world-heath-nlp-computer-vision/ The way we train AI is fundamentally flawedThe process used to build most of the machine-learning models we use today can’t tell if they will work in the realContinue readingWhat I Read: The way we train AI is flawed

What I Read: How DAGs grow

By Andrew Fairless on February 14, 2021January 18, 2021

https://greatexpectations.io/blog/deeper-wider-thicker/ How DAGs grow: Deeper, wider, and thickerNovember 16, 2020 “Over time, this turns into a steady, compounding creep in the maintenance time that you’re putting into the project…. StuffContinue readingWhat I Read: How DAGs grow

What I Read: long-term symptoms of Covid-19

By Andrew Fairless on February 14, 2021January 18, 2021

https://www.vox.com/22166236/long-term-side-effects-covid-19-symptoms-heart-fatigue The many strange long-term symptoms of Covid-19, explainedby Lois ParshleyDecember 15 2020 9:27 PM “…preliminary research suggests that somewhere between 10 percent and 88 percent of Covid-19 patients willContinue readingWhat I Read: long-term symptoms of Covid-19

What I Read: Mismatches between Optimization Analyses and Deep Learning

By Andrew Fairless on February 13, 2021January 14, 2021

http://www.offconvex.org/2020/10/21/intrinsicLR/ Mismatches between Traditional Optimization Analyses and Modern Deep LearningZhiyuan Li and Sanjeev AroraOct 21, 2020 “You may remember our previous blog post showing that it is possible to doContinue readingWhat I Read: Mismatches between Optimization Analyses and Deep Learning

What I Read: US Government Will Pay Doctors to Use AI Algorithms

By Andrew Fairless on February 13, 2021January 14, 2021

https://www.wired.com/story/us-government-pay-doctors-use-ai-algorithms/ Tom SimoniteBusiness11.10.2020 07:00 AMThe US Government Will Pay Doctors to Use These AI AlgorithmsThe artificial intelligence programs can diagnose eye disease in diabetics and complications in stroke patients. “TheContinue readingWhat I Read: US Government Will Pay Doctors to Use AI Algorithms

What I Read: Why is life expectancy in the US lower?

By Andrew Fairless on February 12, 2021January 14, 2021

https://ourworldindata.org/us-life-expectancy-low Why is life expectancy in the US lower than in other rich countries?by Max RoserOctober 29, 2020 “Why do Americans have a lower life expectancy than people in otherContinue readingWhat I Read: Why is life expectancy in the US lower?

What I Read: Why is dbt important?

By Andrew Fairless on February 12, 2021January 14, 2021

https://stephen.sh/posts/why-is-dbt-so-important Why is dbt so important? “Last summer, we migrated Monzo’s entire analytics infrastructure to dbt from a homegrown solution. This took significant effort, but I’m glad we did it.Continue readingWhat I Read: Why is dbt important?

What I Read: Structural Time Series

By Andrew Fairless on February 11, 2021January 13, 2021

https://structural-time-series.fastforwardlabs.com/Structural Time SeriesFF16 · October 2020 “We will describe a family of models—Generalized Additive Models, or GAMs—which have the advantage of being scalable and easy to interpret, and tend toContinue readingWhat I Read: Structural Time Series

Author: Andrew Fairless