Gradient descent is used in many ways at Tesla pic.twitter.com/7EBRtud6fF
— hardmaru (@hardmaru) November 28, 2019
Gradient descent is used in many ways at Tesla pic.twitter.com/7EBRtud6fF
— hardmaru (@hardmaru) November 28, 2019
After my CV, personal and institution website, Google Scholar, ResearchGate, Publons, LinkedIn, Orchid, Web of Science, Scopus, Pure, Academia, I can’t wait for the next tool to simplify managing my academic profile
— Maarten van Smeden (@MaartenvSmeden) November 26, 2019
Data science education: “Hyperparameter Optimization of Recurrent Neural Networks for Sentiment Analysis in Automated Speech Recognition Models”
— Brooke Watson Madubuonwu (@brookLYNevery1) November 25, 2019
Data science jobs:pic.twitter.com/B9BpUJCpZp
“We fail to reject the null hypothesis that you would enjoy receiving this and all future promotional emails.”
— Sean J. Taylor (@seanjtaylor) November 20, 2019
— Companies
Why do I spend my time making these? pic.twitter.com/1xZvqZwepE
— Chelsea Parlett-Pelleriti (@ChelseaParlett) November 18, 2019
Literally all I do as a statistician:
— Rafael Irizarry (@rafalab) November 17, 2019
No.
No.
That's not the definition of a p-value.
No.
Trending towards significance is not a thing.
No.
No pie charts!
That only works if data is normal.
No.
That's logistic regression not AI.
No.
Your "novel" method was invented in 1918.
No. https://t.co/oXiBrgM5oY
Interviewer: How would you efficiently sort a list of value?
— Chris Albon (@chrisalbon) November 17, 2019
Me: .sort()
Interviewer: No, I mean—
Me: pic.twitter.com/cpmP3qTuMS
Literally all I do as a data scientist:
— Chris Albon (@chrisalbon) November 17, 2019
No.
No.
Use OLS.
No.
Don’t do that.
Use median.
No.
You don’t need deep learning.
No.
You can get that model off the shelf.
No. https://t.co/YhoJburv71
Meanwhile inside the Chinese University of Hong Kong pic.twitter.com/PLh5WnAGPm
— hardmaru (@hardmaru) November 16, 2019
I provide all my data with dates formatted as "01%2019%11", because people need to learn that everything is hopeless.
— Nihilist Data Scientist (@nihilist_ds) November 13, 2019
Small sample sizes make the world seem much more interesting than it really is. Measure anything well enough and the answer is just a depressingly inevitable “maybe”. #DataScience #rstats #pydata
— Nihilist Data Scientist (@nihilist_ds) November 5, 2019
The most cost-effective way to defeat the Terminators is to introduce a NaN in a SkyNet training data example
— François Chollet (@fchollet) November 1, 2019