Asking speakers to submit draft slides is about the poorest progress metric you can pick. I could glue together random decent-looking slides that'd make absolutely no sense. On the other hand this talk (see image) is 80% done. pic.twitter.com/O42HNntflz
— Gregor (@ghohpe) January 18, 2021
"everyday Americans make strong moral distinctions among types of data, even when they are told data predict consumer behavior" @BarbaraKiviat shows how Americans adjudicate the fairness of using different data for lending decisions & car insurance pricing https://t.co/CX8odtS92e pic.twitter.com/hz7MJVVUsX
— Dan Hirschman (@asociologist) January 20, 2021
Are night lights (NL) a reliable proxy for local GDP?
— Sam Asher (@thesamasher) January 21, 2021
An answer, in our paper “Development Research at High Geographic Resolution” aka the SHRUG paper (forthcoming at WBER). 🧵1/14
TL;DR: don’t trust existing GDP elasticities. With @paulnovosad @tobiaslunt @ryu_matsuura pic.twitter.com/dpRUy5Hjvy
Amazing map showing the long term effect of Germany’s partition, on religious beliefs.
— Lionel Page (@page_eco) January 14, 2021
ht @urbanthoughts11 pic.twitter.com/VNtRQOzkHP
It takes a 𝙡𝙤𝙣𝙜 time to live down the effects of hatred. Areas in Germany with more antisemitism dating back to 1349 have lower development today because they still avoid banking, mortgages & finance due to their historical associations with antisemitic stereotypes of Jews. pic.twitter.com/J6FwqhaBo0
— Ethan Mollick (@emollick) January 12, 2021
Instead of proposing to do something for no money, that's easy, in exchange for learning, I'd really recommend people ask folks they want to work with "What hard thing do you have no time for that I could go research & figure out?"
— Suhail (@Suhail) January 21, 2021
I am always willing to pay people for outcomes.
In the late 1960s, you could rent a megabyte storage for your mainframe.
— Grady Booch (@Grady_Booch) January 21, 2021
For $18,000.
A month.
While I really like #GithubActions and Gitlab #CI, I do wonder: What about sustainability/energy consumption? Is this an issue devs/devops should consider? Is it already adressed by @github @gitlab? #webdev #sustainability #bitsbaume #gitlab #github pic.twitter.com/znUSmiiahr
— Matthias Andrasch ♻️ (@m_andrasch) August 1, 2020
Does anyone know of a good back-of-the-envelope estimate of the environmental impact of continuous integration?
— Seth Axen 🪓 (@sethaxen) December 30, 2020
And for those who wonder about it, data centers used about 2% of US and global electricity circa 2005, but it's now down to under 1%.
— Jonathan Koomey (@jgkoomey) January 9, 2021
You can find youtube tutorials of Fabio Canova and Filippo Ferroni Empirical macro toolboxhttps://t.co/ChPqatfH2O
— Alessia Paccagnini 👩🏫📚💶📈💻🍕⚽🐱🐶🎥 🎶🌍 (@Alessia_metrics) January 21, 2021
👇👇👇https://t.co/59YZzYyayW#EconTwitter #Econometrics #VAR #EmpiricalMacro #PhDEconomics
.@FAppliedmacro
This is what overemphasizing math when learning ML can lead to.
— Radek Osmulski (@radekosmulski) January 21, 2021
Not a pretty picture 👇 pic.twitter.com/xJMxbsA1nT
“Data Science versus Classical Inference: Prediction, Estimation, and Attribution”, honouring Prof. Brad Efron's International Prize in Statistics in 2019: International Statistical Review: Vol 88, No S1 https://t.co/Ik141AAq2L
— Fırat Melih Yılmaz (@fratmelhylmaz) January 15, 2021
Probably one of the best free resources I've found online!
— Santiago (@svpino) January 19, 2021
An introduction to linear algebra for machine learning with Python 🐍.
Bookmark this link in your browser and use it as a reference whenever you need it.
https://t.co/n6qjJ3KXvi via @CodeBug88 pic.twitter.com/PIP90trXCo
It's not always clear what you can do to help on an early-stage project, so I made a list of possible contributions to MCX at this stage:
— Dr. Rémi Louf 👾 (@remilouf) January 20, 2021
- new distributions
- neural network layers
- model simplifications
- remove constants from loglikelihoodhttps://t.co/abx7W985FQ
On Tue 21, Quantitative Risk Management will start.
— Pasquale Cirillo (@DrCirillo) April 19, 2020
These are the topics of the different lessons (minor changes possible), which will appear here: https://t.co/R4XFiKCgWS
Lesson 1: The Philosophy of Risk 1
Lesson 2: Risk Measures and Functionals
Lesson 3: Extreme Value Theory 1
The problem with ML education is the assumption that datasets are static, and models are the only way to make progress.
— Josh Tobin (@josh_tobin_) January 21, 2021
Thinking that training is the last step is kind of like thinking the world is flat. Just because you can't see the outer loop doesn't mean it's not there :) pic.twitter.com/ezPtK5fS97
Everything you wanted to know about the #hydrogen economy but were too busy to research.
— Gniewomir Flis (@gnievchenko) September 28, 2020
Part 2: International hydrogen markets could be a thing, but don’t bet on hydrogen shipping
1/18
Economic forecasts, in a nutshell (via @mattyglesias on the left) pic.twitter.com/BD1lB6vQJl
— Arthur Charpentier (@freakonometrics) December 10, 2020
0/ A holiday economic theory reading list. Some of my favorite pieces on theory that can be read with minimal sweat, but with the maximal intellectual reward. In no particular order:
— Rohit Lamba (@rohlamba) December 19, 2020
Turns out Journal of Economic Perspectives has a page where articles are classified by what type of econ course they could be useful for. Looking for a JEP article for your introductory or environmental course? Just two clicks and you'll get a list!https://t.co/iZl4qzZjrg
— Tatyana Deryugina (@TDeryugina) January 21, 2021
Paper presenting https://t.co/oVhgRcCsb8 coming soon to the Journal of Economic Education! Accepted this morning! #TeachEcon #EconTwitter #UBCO
— Julien Picault (@PicaultJ) January 8, 2021
Thanks to the 2 amazing referees! Suggestions improve the website greatly!
Problem-solving is central to IT - there so much to learn about technology, so that the end-goal sometimes fades. Surprisingly, the solution can be no-code and no-software, which can be hard to admit. https://t.co/tfXnK6GU94
— Evgeny Pogrebnyak (@PogrebnyakE) January 21, 2021
Помоги Даше-разработчице понять, на каком уровне протекает абстракция pic.twitter.com/D1qyViToXP
— Табличка «Сарказм» (@glorphindale) January 20, 2021
I was at Amzn in 2000 when the internet bubble popped. Capital markets dried up & we were burning $1B/yr. Our biggest expense was datacenter -> expensive Sun servers. We spent a year ripping out Sun & replacing with HP/Linux, which formed the foundation for AWS. The backstory:
— Dan Rose (@DanRose999) January 8, 2021
I started to deep-dive into @Felienne's book: the programmer's brain.
— Michaela Greiler (@mgreiler) January 8, 2021
It's fantastic. Packed with solid, evidence-based info on how we learn and how we can better read, write, and understand code.
I have to get her on the @se_unlocked podcast! https://t.co/JHYnAEP6jG
— Yan Cui is making the AppSync Masterclass (@theburningmonk) December 22, 2020
Building microservices is easy. What's hard:
— James Hickey 🇨🇦👨💻 (@jamesmh_dev) January 4, 2020
- Discovering proper boundaries
- Integrating services (Messaging vs RPC)
- Error handling (resiliency)
- Sociotechno concerns (team boundaries, org changes)
Can you think of any more?#microservices #dddesign #softwareengineering
On another thread someone raised the old question of 'are microservices just SOA'. Here is a slide from my Practical Messaging course on that (course runs again Mon-Tue sure we can let you in at short notice, see pinned tweet): pic.twitter.com/DfIj9GE6rx
— Ian Cooper 💙 (@ICooper) January 23, 2021
Top #python projects on #github by category: use #requests/#scrapy to load data from #flask/#django into #pandas and process it with #tensorflow/ #keras on machines under #ainsible/ #docker-compose while reading into awesome-python/system-design-primer.
— Evgeny Pogrebnyak (@PogrebnyakE) September 4, 2018
"2008 to 2013-2015 should be known as the lost years of Python because so much opportunity and energy was squandered." https://t.co/SEXRa39E7R
— Evgeny Pogrebnyak (@PogrebnyakE) January 15, 2020
Systems thinking & complexity theory - wrangling with wicked problems.
— Dawn Ahukanna (@dawnahukanna) January 20, 2021
Then came across a black & white recorded lecture from 1977 by Donella Meadows, talk about being ahead of her time, pre-YouTube. She used physical transparency slides too - https://t.co/x6v1agrw9T
Back to writing my book on scientific visualisation using #matplotlib. Working now on the chapter on color. More at https://t.co/hh6IhtSzkc pic.twitter.com/KfT2MxryDj
— Nicolas P. Rougier (@NPRougier) January 15, 2021
— Evgeny Pogrebnyak (@PogrebnyakE) January 17, 2021
This is the most detailed map of our Solar System to date ✨ pic.twitter.com/n8MXeYWX8g
— Jasmine 🌌🔭 (@astro_jaz) January 16, 2021
#Solar will account for the largest share of planned new U.S. #electricity capacity in 2021, growing by 39%. #Windenergy capacity will increase by 31% in 2021. https://t.co/DhAS8kUjMT pic.twitter.com/vjdjEfZvqM
— EIA (@EIAgov) January 21, 2021
Does anyone know a good intuitive explanation for the central limit theorem? I realized the other day that even though I use it all the time I can't really justify *why* it's true.
— Stephan Hoyer (@shoyer) January 23, 2021