🧮 Life tip: Make and use project templates.
— Mara Averick (@dataandme) July 25, 2019
"How Do You Organise Your R Project? This Is What We Do." https://t.co/n1DKvlBkBp #rstats via @telethonkids
🧮 Life tip: Make and use project templates.
— Mara Averick (@dataandme) July 25, 2019
"How Do You Organise Your R Project? This Is What We Do." https://t.co/n1DKvlBkBp #rstats via @telethonkids
Watch "Visualizing uncertainty with hypothetical outcomes plots" by @ClausWilke Claus Wilke
— RStudio (@rstudio) July 25, 2019
from rstudio::conf(2019)
🎦 https://t.co/XwqGeNSXAj
Learn more about rstudio::conf(2020) in San Francisco: https://t.co/BGi7aYWwty #rstats #DataScience pic.twitter.com/agzCu9DFyv
We just published a new tutorial for Image Segmentation, using a U-Net style architecture (and a pretrained MobileNet). Runs pretty quick, too.
— Josh Gordon (@random_forests) July 24, 2019
Nice work, @arjun_dcunha! https://t.co/w4NFV12yAg pic.twitter.com/BNR5j9VaZ4
Ordinary Least Squares https://t.co/eZ2bbpDzwV pic.twitter.com/kEIkMmWecs
— Chris Albon (@chrisalbon) July 24, 2019
This book has the most wonderful walk-through of that fyi Code: The Hidden Language of Computer Hardware and Software https://t.co/qSJzPoV3rF
— Jeremy Howard (@jeremyphoward) July 24, 2019
Chi-Squared For Feature Selection https://t.co/eZ2bbpDzwV pic.twitter.com/3XPTSpse80
— Chris Albon (@chrisalbon) July 23, 2019
This is a powerful abstraction for image data augmentation that generalizes MixUp, Cutout, CutMix, RICAP, and more, and allows annealing of the amount of augmentation during training (to support curriculum learning)https://t.co/8WZjoYeoYI pic.twitter.com/fkp9ShLAdK
— Jeremy Howard (@jeremyphoward) July 20, 2019
🙌 @tladeras & @datapointer have made a their course FREE using {decampr} & @_inesmontani's free and open course format…
— Mara Averick (@dataandme) July 19, 2019
🥾 "RBootcamp · A free online course about the basics of the tidyverse" https://t.co/fpHuN8d9q7 #rstats #tidyverse pic.twitter.com/gfukOiYZzz
Simpsons Paradox https://t.co/eZ2bbpDzwV pic.twitter.com/1n9cZiz7Er
— Chris Albon (@chrisalbon) July 19, 2019
Just gave a talk on my recent line of work on ***Robust Deep Learning Under Distribution Shift*** at @SimonsInstitute. Topics incl. impossibilities, label shift, detection, importance weighting & domain-adversarial methods https://t.co/JrOLiV0jXX
— Zachary Lipton (@zacharylipton) July 18, 2019
Machine Learning in a company is 10% Data Science & 90% other challenges
— Andrew Trask (@iamtrask) July 18, 2019
It's VERY hard. Everything in this guide is ON POINT, and it's stuff you won't learn in an ML book
"Best Practices of ML Engineering"
This is a lifesaver #100DaysOfMLCode projecthttps://t.co/3FTq3zcZNf pic.twitter.com/TAyVvWezAz
data.table 📦 users: Wondering how to use the .SD symbol when grouping your data? Check out my latest Do More With R video and article:#rstats #rdatatable https://t.co/xLoVQD5Tcx
— Sharon Machlis (@sharon000) July 18, 2019