How many random seeds are needed to compare #DeepRL algorithms?
— Pierre-Yves Oudeyer (@pyoudeyer) July 6, 2018
Our new tutorial to address this key issue of #reproducibility in #reinforcementlearning
PDF: https://t.co/7eHOzhtLuC
Code: https://t.co/0CRRM8RYYr
Blog: https://t.co/rYWM5zPYZB#machinelearning #neuralnetworks
today's #plotswithchristine takes a closer look at my #FourthofJuly UFO sightings chart: a "ridgeline plot" showing sightings year-by-year + annotations for some of the larger spikes. still not sure how i feel about ridgeline plots 🤔#dataviz
— Christine Zhang (@christinezhang) July 6, 2018
data+code: https://t.co/TGAzzUusOw pic.twitter.com/GlGqEgnpOY
Fastest way to train on CIFAR10 - now available on a PC near you! 🙂
— Radek (@radekosmulski) July 5, 2018
This is a 🔋 included docker setup featuring recent work by @GuggerSylvain & @jeremyphoward (training with AdamW and the 1 cycle policy). Very excited by the development!https://t.co/C5QpkDFOwH pic.twitter.com/JA2NkeL212
I wrote a tutorial on leveraging #DeepLearning to build a powerful image search engine quickly. It includes a notebook to walk you through and a codebase to play with. Also comes with a shoutout to @jeremyphoward and his great class on the topic! https://t.co/fRJHpMcq3h
— Emmanuel Ameisen (@EmmanuelAmeisen) July 5, 2018
The slides from my ⚡️talk at @rencontres_R about {purrr} are online !
— Colin Fay 🤘 (@_ColinFay) July 5, 2018
🔗 : https://t.co/YUPYW2V6lA#RR2018 #RStats #RStatsFR pic.twitter.com/pOd22Oxr4E
New blog on GPU accelerated XGBoost, faster, and handles larger scale with GPU acceleration https://t.co/prN3hlqBUZ
— XGBoost (@XGBoostProject) July 5, 2018
✨ viz *and* interactive:
— Mara Averick (@dataandme) July 4, 2018
"An animated guide to Frequency Trails (aka Joyplots)" 👨🎤 @luiscarlihttps://t.co/YhRGbolwG2 #dataviz #infovis pic.twitter.com/cxnt7CZuUn
Check out @stephaniejyee and @tonyhschu's stunning visual guide explaining the tradeoff between bias and variance in model tuning https://t.co/fHGdY9k6Id
— Kaggle (@kaggle) July 4, 2018
Second #blogdown post in my #BayesianBabySteps series - intro to using Laplace approximation to model #NFL score differentials, determining the value of passing efficiency relative to rushing with EPA from #nflscrapR and the effect of strong priors #rstats https://t.co/98cTHnKH9z pic.twitter.com/33ZulJdC4o
— Ron Yurko (@Stat_Ron) July 4, 2018
a v. special #July4 #plotswithchristine adds a dash of "chart junk" to my usual #dataviz fun––UFO sightings peak on #IndependenceDay 👽🛸👾
— Christine Zhang (@christinezhang) July 3, 2018
data+code: https://t.co/TGAzzUusOw
h/t @dhmontgomery (title+#rstats tips), @_cingraham (title+viz inspiration), @thejefflarson (emoji) pic.twitter.com/7PEkCT1eFP
Brush up on @thomasp85's animation 🔥 step-by-step before #useR2018
— Mara Averick (@dataandme) July 3, 2018
🎞 “Taking control of animations in R and demystifying them in the process”https://t.co/Qoeeqq27Oc #rstats pic.twitter.com/KDoJ7ILvB2
Tried my hand at creating an animated plot for #TidyTuesday this week. I've been needing to use a lot of #spatial libraries lately for work. Great way to practice. Also tried to be a little more analytical with a loess regression #rstats #tweenr #tidyverse https://t.co/FBTXN7JfVo pic.twitter.com/zhhmsGYvVk
— Dylan McDowell (@dylanjm_ds) July 3, 2018
