"An Academic's Observations from a Sabbatical at Google," Adam Barker: https://t.co/tgWOvkhP1z
— Miles Brundage (@Miles_Brundage) August 29, 2018
"An Academic's Observations from a Sabbatical at Google," Adam Barker: https://t.co/tgWOvkhP1z
— Miles Brundage (@Miles_Brundage) August 29, 2018
This is an important point about how research benefits from good engineering practices: https://t.co/bp9d4xTghE
— Rachel Thomas (@math_rachel) August 29, 2018
#Data Management: How to manage your #data. Learn more: https://t.co/BbdCdPgfa7 #datascience #analytics #bigdata pic.twitter.com/U4U7vDji8E
— Booz Data Science (@BoozDataScience) August 28, 2018
Well @GaryMarcus, why do you think this is a problem with "deep learning" as opposed to a shortcoming in our current deep learning networks? I predict these problems will be completely solved within the DL paradigm.
— Thomas G. Dietterich (@tdietterich) August 28, 2018
new post for my ask-a-data-scientist advice column: What You Need to Know Before Considering a PhD https://t.co/SUNpHitdot
— Rachel Thomas (@math_rachel) August 27, 2018
I literally had to argue with a reviewer about showing a full time series of data in a paper. They argued reporting summary statistics was enough. Nope. It really isn’t. Datasaurus rex is my favorite example for illustrating why... pic.twitter.com/eHl2KX5hV8
— Dan Weaver (@DanWeaver_ca) August 27, 2018
“Why love generative art?”
— hardmaru (@hardmaru) August 27, 2018
A beautiful essay by @artnome https://t.co/B06JOWu5nq pic.twitter.com/XhdmteLKdt
So this portrait produced by a poorly-trained GAN will fetch $10K+ at Christie's.
— hardmaru (@hardmaru) August 27, 2018
I like the signature at the bottom:
𝒎𝒊𝒏 𝑮 𝒎𝒂𝒙 𝑫 𝔼𝒙 [𝒍𝒐𝒈 𝑫 (𝒙))] + 𝔼𝒛 [𝒍𝒐𝒈(𝟏 − 𝑫(𝑮(𝒛)))] pic.twitter.com/IXWREEzlZh
“The only bright spot [among the Humanities] is linguistics, the rare field that directly bridges the humanities and the sciences.” (Linguistics is 2nd only to Exercise Science in majors growth rate—1st derivative—in 2000s!) https://t.co/Oxhhq0pqS3
— Stanford NLP Group (@stanfordnlp) August 26, 2018
I like Notebooks and they can be useful even in production-grade environments (see “Beyond Interactive: Notebook Innovation at Netflix” https://t.co/BJjjPQwbpT). However, all of @joelgrus points, especially the one about hidden state, are 100% valid and should be addressed https://t.co/ANUh7wixkX
— Xavier 🎗🤖🏃 (@xamat) August 26, 2018
Great example of a (sleep-deprived) personal data project! https://t.co/xWILkZbq5b
— Data Science Renee (@BecomingDataSci) August 26, 2018
This is not necessarily a bad thing depending on the task at hand, but it does highlight obvious limitations of what they can be used for. We shouldn’t be surprised if our algorithms behave ridiculously when we deploy them outside of the data distribution it was trained to model.
— hardmaru (@hardmaru) August 26, 2018