Tag: misc

Sketch-RNN Painthttps://t.co/WdU3B6aTYI pic.twitter.com/OUgIEVjk43

— hardmaru (@hardmaru) September 13, 2018

Junior Engineer: I found the problem!

Senior Engineer: I found *a* problem.

Principal Engineer: I may have found a problem.

Manager: Hey how’s the search for that problem going?

— David Robinson (@drob) September 13, 2018

Histogram of P-values (rounded, presumably, to the nearest 0.01) published in millions of scientific studies. Hmm. Great, provocative talk by @StatGarrett at #earlconf pic.twitter.com/42MegOhjsQ

— David Smith (@revodavid) September 12, 2018

#numpy is an irreplaceable part of every practitioner's Deep Learning toolkit, and the best way to learn NumPy that I know of is this crash course

If NumPy is new to you - definitely include this early in your #100DaysOfMLCode - you won't regret it!https://t.co/2mqLDAgQuN pic.twitter.com/9rxPYe69qk

— Trask (@iamtrask) September 11, 2018

There are cases in which relational databases are the right, or at least acceptable thing to use. I still design relational databases when they fit the need.

I really don't like this kind of marketing in our industry that tries to pit people against each other, unnecessarily. https://t.co/gkaI0jsGDw

— Data Science Renee (@BecomingDataSci) September 11, 2018

GitHub repo of jupyter notebooks from a Columbia Journalism course on algorithmic data analysis in journalism & journalism coverage of algorithms: https://t.co/DsvwXS68DA

— Rachel Thomas (@math_rachel) September 10, 2018

Generative Art Finds Its Prodigy, by @artnome with @manoloidee. “The most beautiful parts of the work are born from the errors. From these errors, I take an idea and it stays. They are beautiful errors.” https://t.co/5iEmkQBV87 pic.twitter.com/5lDj0ibTC4

— hardmaru (@hardmaru) September 10, 2018

Dangerous habit: Play around with an algorithm in a Jupyter notebook and check if the output looks “reasonable” instead of writing a proper unit test. It’s not a substitute. In the long run you’ll save more time writing tests.

— Denny Britz (@dennybritz) September 10, 2018

How to get ML papers rejected in 2003. https://t.co/2d1dgsJXNO pic.twitter.com/oiaH3ouuwn

— hardmaru (@hardmaru) September 9, 2018

Wherein @benmschmidt and digital humanities fam call major BS on WikiLeaks 🐮💩…
A+ @callin_bull — @MaciejEder's paper deserves serious ⬆ in impact factor!
📄 https://t.co/KPlwAgnjiv
🐦 by @ben_fry https://t.co/RxBYCLu1K0 pic.twitter.com/yyKGKsl8gc

— Mara Averick (@dataandme) September 8, 2018

Thrilled to launch a big project today: ANATOMY OF AN AI SYSTEM. It's a large map & long-form essay about Amazon's Echo, and the full stack of capital, labor, and natural resources used in AI. It's a collab with @TheCreaturesLab, who is a visual genius ✨ https://t.co/Zj9Xv6SxFb

— Kate Crawford (@katecrawford) September 7, 2018

This is marvelous and counter-intuitive advice from someone who's a great role model for founders. More links in the thread. https://t.co/cm1APASma0

— Jeremy Howard (@jeremyphoward) September 7, 2018