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Prikvačeni tweet
Great news! Truly enjoyed writing this with my buddy
@bgreenwell8 & learned so much in the process. Many thanks to@CRC_MathStats & especially@crcgrubbsd for our "minor" timeline adjustments
. Hope the #rstats community benefits from the work!#DataScience#MachineLearninghttps://twitter.com/crcgrubbsd/status/1194348251106951168 …
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Must read - http://Booking.com paper on their
#MachineLearning process: - loss gains vs biz metric gains - relative impact of all models - RCTs for model impact comparison - dealing with latency in production
: http://ow.ly/b0FN50y872m
More reads: http://ow.ly/VF3E50y878a pic.twitter.com/2tKiyjO3Cf
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Bradley Boehmke proslijedio/la je Tweet
Glad I was part of this team! For anyone who missed it, you can check the material made available by
@bradleyboehmke and@rstudio here
#rstudioconfhttps://twitter.com/bradleyboehmke/status/1223262217967230977 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bradley Boehmke proslijedio/la je Tweet
floodsung / Deep-Learning-Papers-Reading-Roadmap Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap …
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Great time teaching
#deeplearning with keras & tensorflow workshop at#rstudioconf
support by @OmaymaS@Rick_Scavetta@dougashton@danielfrg@cdhowe &@rstudio Ed team,@rnt_cole@alexkgold & others...

Material is CC BY 4.0: http://ow.ly/npSk50y8FJX ...enjoy! #rstatsHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bradley Boehmke proslijedio/la je Tweet
Excited to announce at
#rstudioconf2020 that#sparklyr is now hosted within the@LinuxFoundation and LF AI! Site: http://sparklyr.ai Blog: http://blog.rstudio.com/2020/01/29/sparklyr-1-1 … Slides: http://rpubs.com/jluraschi/rsconf-2020 … Also, sparklyr 1.1 now in CRAN, adds supports for@DeltaLakeOSS with#rstats!pic.twitter.com/ImYL2r7tKy
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Bradley Boehmke proslijedio/la je Tweet
Swing by our table at
#RStudioConf to get our#DataScience titles at 20% off! Get the latest books from@cpsievert,@bradleyboehmke &@bgreenwell8,@rafalab,@old_man_chester &@rudeboybert and more!#RStats#RPackages#RShiny#RProgramming#Statistics#RStudio @rtsudio#UseRpic.twitter.com/wsC9AQ0S2BHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bradley Boehmke proslijedio/la je Tweet
The latest h2o
#rstats package, v3.28.0.2, is now on CRAN! Lots of new features to check out, including:
Hierarchical GLMs
New #AutoML leaderboard metrics
Parallel grid search (super speedup!)
#XGBoost updates
Read more here:https://www.h2o.ai/blog/h2o-release-3-28-yu/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Bradley Boehmke proslijedio/la je Tweet
Interesting paper showing how dozens of studies have accidentally leaked large amounts of data from train->test dataset, by duplicating data items prior to doing a random split.https://twitter.com/Gillesvdwiele/status/1219194600994283520 …
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Bradley Boehmke proslijedio/la je Tweet
Geek alert
I’m super excited to be back at @rstudio#RStudioConf next week in SF
Hoping to meet lots of new people any see some familiar faces — say hi!
I’ll be a TA in @bradleyboehmke‘s#DeepLearning workshop on both days. He’s created an aces training program
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Bradley Boehmke proslijedio/la je Tweet
“Be curious. Read widely. Try new things. I think a lot of what people call intelligence boils down to curiosity.” - Aaron Swartz
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Neural network hyperparameter optimization can be daunting...but it can also "be reasonably quick if one searches for clues in the test loss early in training." This paper is great for anyone trying to put some logic behind
#deeplearning model tuning. http://ow.ly/GMtQ50xTVUU pic.twitter.com/IXRvLq3KcS
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#deeplearning tip: don't just rely on a constant or decaying learning rate, often cyclical learning rates can improve performance. Read this paper for the why and how. http://ow.ly/8rEQ50xTWCg pic.twitter.com/QTkyIuwOwk
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Getting excited. Partly because this title slide is far more inviting then the cold and dreary Ohio winter day outside my window!
#rstats#rstudioconfpic.twitter.com/JK5oEeAKXP
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Learning curve issue #7: Underrepresented validation data Val loss < train loss, no matter how many iterations performed. Often from data leakage or poor sampling procedures. Try: 1. ✓ for dup obs 2. ✓ for data leaks 3.
k-fld CV / bootstrap
#MachineLearning#DataSciencepic.twitter.com/NlQ6aBxNEA
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Bradley Boehmke proslijedio/la je Tweet
Enjoyed this 2016 article by
@seb_ruder on#deeplearning optimization algorithms for gradient descent, covers stochastic methods to distributed training -- Definitely still relevant in 2020! https://ruder.io/optimizing-gradient-descent/index.html …pic.twitter.com/4X89dC1w8UHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
R tip: use DESCRIPTION file in any
#rstats project/repo (does NOT have to be a
) to simplify dependency install for end users. End user simply runs devtools::install_deps() to install all
s listed as Imports
@hadleywickham's
s (i.e. https://github.com/hadley/ggplot2-book …) are
examplesHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Learning curve issue #6: Underrepresented validation data Train loss looks to be learning but valid loss shows noisy movements and little or no improvement. Try: 1.
obs to validation set
2.
k-fld CV / bootstrap
#MachineLearning#DataSciencepic.twitter.com/KQSqGRVwqe
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Bradley Boehmke proslijedio/la je Tweet
What I did over my winter break! It gives me great pleasure to share this summary of some of our work in 2019, on behalf of all my colleagues at
@GoogleAI &@GoogleHealth.https://ai.googleblog.com/2020/01/google-research-looking-back-at-2019.html …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
When your
#rstats#MachineLearning model says this, turn to the vip
! https://twitter.com/bgreenwell8/status/1215394435942535168 …pic.twitter.com/rH10d8hFKEHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Excited to see the
@DataSkeptic podcast will be focusing on interpretable#MachineLearning in 2020. Quite fitting that the first guest was@ChristophMolnar!#XAIHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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