Simon Couch@simonpcouch

he/him - writing statistical software @posit_pbc (née RStudio)🥑 on the other sites @ simonpcouch

 Chicago, IL, U.S.A.
simonpcouch.com
Joined September 2019
72 Photos and videos
Some news: I've just open-sourced the draft of a book I'm working on about how #rstats tidymodels users can make their code run faster without sacrificing predictive performance! simonpcouch.com/blog/2024-10…

ALT Scrolling through the Quarto website for Efficient Machine Learning with R. I quickly scroll through the preface before toggling open the table of contents.

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Released a cauldron of R code today 🎃👻 Introducing Kolmogorov-Arnold Networks for Time Series in R! It's an R package called {kantime}, a super experimental port of Nixtla's {neuralforecast} from Python to {modeltime} in R
frankiethull/kantime Bindings for Nixtla's neuralforecast Library in R, specifically KANs, to use with {modeltime} package. Nixtla's KAN is called from R via {reticulate}, which is then ported into {parsnip} and bridged to {modeltime}.

ALT frankiethull/kantime Bindings for Nixtla's neuralforecast Library in R, specifically KANs, to use with {modeltime} package. Nixtla's KAN is called from R via {reticulate}, which is then ported into {parsnip} and bridged to {modeltime}.

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Monitoring Models in Production is essential to ensure accuracy, detect drift, and maintain fairness over time. For more, check out our recent blog by Myles Mitchell on "Vetiver: Monitoring Models in Production". #DataScience #MLOps #Rstats jumpingrivers.com/blog/vetiv…

Vetiver: Monitoring Models in Production

Part 3 in our series of blogs on vetiver for MLOps. Having previously introduced the modelling and deployment steps of the MLOps workflow, we now consider the maintenance of a model in production....

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This is tomorrow! #rstats folks, come through!
Simon Couch@simonpcouch
23 Oct 2024
I'll be giving a free virtual talk on speeding up your #rstats tidymodels code at R/Pharma 2024 this Tuesday and would love to see you there! I'll also be announcing a new project.👀 Register here: rinpharma.com/
A title slide reading "From hours to minutes: Accelerating your tidymodels code." Beside the text is a hex wall containing stickers for core packages like parsnip, recipes, and tune.

ALT A title slide reading "From hours to minutes: Accelerating your tidymodels code." Beside the text is a hex wall containing stickers for core packages like parsnip, recipes, and tune.
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Simon Couch retweeted
Carlos Alberto Haro@h1sort
25 Oct 2024
i like R
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I'll be giving a free virtual talk on speeding up your #rstats tidymodels code at R/Pharma 2024 this Tuesday and would love to see you there! I'll also be announcing a new project.👀 Register here: rinpharma.com/
A title slide reading "From hours to minutes: Accelerating your tidymodels code." Beside the text is a hex wall containing stickers for core packages like parsnip, recipes, and tune.

ALT A title slide reading "From hours to minutes: Accelerating your tidymodels code." Beside the text is a hex wall containing stickers for core packages like parsnip, recipes, and tune.

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The #rstats tidymodels team is hard at work implementing postprocessing! There will be changes in almost all of our core packages as well as an entirely new package included in this set of releases. We value your opinion—let us know what you think: tidyverse.org/blog/2024/10/p…
Two ggplot2 dotplots, side-by-side. Both show the true value of an outcome versus the predicted value from a machine learning model. On the left, the "plain" model tends to predict is lower than it actually is, and increasingly so as the true value grows larger. The behavior of the "postprocessed" model is corrected.

ALT Two ggplot2 dotplots, side-by-side. Both show the true value of an outcome versus the predicted value from a machine learning model. On the left, the "plain" model tends to predict is lower than it actually is, and increasingly so as the true value grows larger. The behavior of the "postprocessed" model is corrected.

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Simon Couch retweeted
Rebecca Barter@rlbarter
14 Oct 2024
📢 Tomorrow is the official release of @bbiinnyyuu and my book, Veridical Data Science, with @mitpress. I'm so excited to for physical copies to be out in the world! Get your copy from mitpress.mit.edu/97802620491…
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Updated the documentation for {maize} 🌽 String kernels are the newest addition which were a bit tricky to plant 👨🏻‍🌾 And I'm liking how this table turned out, thanks to @gt_package & gtUtils 🙌🏻
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Winston Chang@winston_chang
9 Oct 2024
Announcing Shiny Assistant, an AI-powered tool that can help you build Shiny applications! shiny.posit.co/blog/posts/sh…

Shiny Assistant

Prototype and build Shiny applications with the help of AI

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Postprocessing is coming to tidymodels! We've got a set of changes for updating model predictions coming to the next version of our #rstats packages. Let us know what you think: tidyverse.org/blog/2024/10/p…

Postprocessing is coming to tidymodels - Tidyverse

The tidymodels team has been hard at work on postprocessing, a set of features to adjust model predictions. The functionality includes a new package as well as changes across the framework.

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{maize} works with {stacks} too! 🌽🥞 {stacks} is part of the tidymodels ecosystem for combining many models into a new ensemble model Here's an ensemble example of three SVMs with different types of kernels 🌽🌽🌽
Ambassador Frank Hull ☤@frankiethull
2 Aug 2024
The dopest parts about {maize}? It jives well with the tidymodels ecosystem! Here, I'm answering a typical question keeping everyone up at night, "what does conformal inference quantile regression prediction intervals look like for a laplacian kernel support vector machine" 🤓
Code snippet of setting up a laplace kernel svm spec, svm wkflow fitting, conformal quantile fit, and create conformal predictions

ALT Code snippet of setting up a laplace kernel svm spec, svm wkflow fitting, conformal quantile fit, and create conformal predictions

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Simon Couch retweeted
Jim Hester@jimhester_
27 Sep 2024
Today marks the 10 year anniversary of my first lintr commit (github.com/r-lib/lintr/commi…) Hard to believe it was 10 years ago Apparently originally I called it styleR, long before the current styler package came into being 😄

Initial commit of styleR · r-lib/lintr@f8fcbe8

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A new release of #rstats broom made it to CRAN yesterday! v1.0.7 includes changes to tidiers for objects from survival, boot, car, and (base) stats. Read more: broom.tidymodels.org/news/in…
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The tidymodels team recently released a set of features for assessing model fairness. I got to drop by the Cascadia #rstats Conf this summer to share about our process in putting that toolkit together, and a recording of the talk is now live! piped.video/watch?v=1wKt-574…

Simon Couch: Fair machine learning

Simon CouchFair machine learningCascadia R Conf 2024Regular talk...

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Slides and #QuartoPub source code: github.com/simonpcouch/casca…

GitHub - simonpcouch/cascadia-24: Source code and slides for "Fair machine learning" at Cascadia R...

Source code and slides for "Fair machine learning" at Cascadia R Conf 2024 - simonpcouch/cascadia-24

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Simon Couch retweeted
Davis Vaughan@dvaughan32
27 Aug 2024
cpp11 0.5.0 is on CRAN 🥳 The main thing to note is that we've removed all non-API R calls, so if you use cpp11 you should no longer get any NOTEs when submitting to CRAN! #rstats cpp11.r-lib.org/news/index.h…
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Bruno Rodrigues
@brodriguesco
18 Aug 2024
Let me take this opportunity to shill the infer #RStats package infer.tidymodels.org/article… read the vignette which explains why charts like the one below can be ignored nowadays (we have very good computers these days)
Prof Lennart Nacke, PhD
@acagamic
15 Aug 2024
How I pick the right statistical test for my experimental variables
Flowchart of commonly used statistical tests from: https://lantsandlaminins.com/statistics-test-flow-chart/

ALT Flowchart of commonly used statistical tests from: https://lantsandlaminins.com/statistics-test-flow-chart/

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This R repo wouldn't be possible without {modeltime} and {tidymodels} 🙌🏻 It shows how easy conformal prediction is in R A nice read if you already have @predict_addict's book and Tidy Modeling with R by @topepos & @juliasilge
Valeriy M., PhD, MBA, CQF
@predict_addict
31 Jul 2024
R fans of conformal prediction, there are some repos translating code for my book into R (courtesy of @frankiethull) I am also going to post a few libraries in R in comments. #confoRmalprediction
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arXiv -> alphaXiv Students at Stanford have built alphaXiv, an open discussion forum for arXiv papers. @askalphaxiv You can post questions and comments directly on top of any arXiv paper by changing arXiv to alphaXiv in any URL!
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