Occasionally you have to read data into #rstats where one observation is split across multiple rows. A handy pattern to fix is to mutate, fill, and filter pic.twitter.com/be7JQNscCE
— Hadley Wickham (@hadleywickham) June 22, 2018
Occasionally you have to read data into #rstats where one observation is split across multiple rows. A handy pattern to fix is to mutate, fill, and filter pic.twitter.com/be7JQNscCE
— Hadley Wickham (@hadleywickham) June 22, 2018
💬 fun code-through feat. rtweet and #tidytext!
— Mara Averick (@dataandme) June 22, 2018
"Awesome Twitter Word Clouds in R" 👩🎨 @LittleMissData https://t.co/uWUGu6HSdj #rstats #dataviz #SoDS18 pic.twitter.com/DGznFOzA1W
This phenomenon can now be reliably replicated as shown in the follow up paper from @lnsmith613. We're now working with @GuggerSylvain to provide guidelines for more models. https://t.co/d2cAE7dDP8 https://t.co/AcUEkQ3CPW
— Jeremy Howard (@jeremyphoward) June 22, 2018
Excited to see @mpjme using @observablehq to teach! https://t.co/IQlz7WwlQl
— Mike Bostock (@mbostock) June 22, 2018
My colleague Raghu has just released "Quantizing deep convolutional networks for efficient inference" - https://t.co/D87ziflTqd
— Pete Warden (@petewarden) June 22, 2018
This white paper covers practical quantization approaches for most common CNNs in @TensorFlow, I think it will be super useful!
New post:
— Guillaume Rousselet (@robustgar) June 22, 2018
Small n correlations + p values = disasterhttps://t.co/KBgRHGCvLg pic.twitter.com/mBe2oRb3Tk
@jakevdp Here's my write up on interactive Altair charts: https://t.co/440rNn34yB#dataviz #python pic.twitter.com/EiVGa3Kr7J
— Matthew Kudija (@mkudija) June 22, 2018
🚀 your team ⇨ R (+ good learning advice)...
— Mara Averick (@dataandme) June 22, 2018
"Teaching the tidyverse to co-workers" ✍️ @astroeringrand https://t.co/UA9YGdvWIt #rstats pic.twitter.com/IsZlBKDQr4
How do you plot 3000 time series? Extract their features and plot the distribution! @robjhyndman #nyhackr pic.twitter.com/j4gcmE6eJe
— Emily Robinson (@robinson_es) June 21, 2018
“Predicting the next Fibonacci number with Linear Regression in TensorFlow.js” by @curiousily https://t.co/FjrKK3UMph #tensorflow #deeplearning #machinelearning
— TensorFlow Best Practices (@TFBestPractices) June 21, 2018
🌟 post for understanding Imports vs Depends:
— Mara Averick (@dataandme) June 21, 2018
🔭 "How R Searches and Finds Stuff" by @surajgupta
🔗 https://t.co/TIpb9OiJZy #rstats pic.twitter.com/rrrTiJLteD
Reproducibility tip of the day: If you're sharing code and data for people to reproduce your work, please release them both under a license that allows reuse. (I'm personally partial to Apache 2.0 and CC-BY-SA.) Unlicensed code + data is protected by copyright & not reusable. 😢
— Rachael Tatman (@rctatman) June 21, 2018