Simon Jackson

@drsimonj

Lead Data Scientist at , empowering people to make good decisions. Love to talk stats, psych, decision making, machine learning, R

Participa desde março de 2015

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  1. Tweet Fixado
    21 de ago

    "Exploring correlations in R with corrr" A blog-post version of my amst-R-dam meetup talk. BONUS: Features DB backend addition by

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  2. retweetou
    8 de dez

    🎁 Day 8 👨‍⚕️ Simon Jackson () 💪 {corrr} for tidy correlations 🔧 {twidlr} for tidy model pipelines 📝 Great blog posts

    Exploring correlations in R with corrr
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  3. retweetou
    28 de nov

    At long last, the parsnip package is on CRAN. parsnip is a unified R interface to models. The first of two blog posts about the package is at

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  4. retweetou
    27 de nov

    🎞 these are so cool! "causalgraphs: R code to generate animated displays of basic causal inference methods" 👨‍💻

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  5. retweetou
    15 de nov
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  6. retweetou
    14 de nov

    🤩 TIL about reticulate::py_install(), meaning I can forget about all these various ways to install 🐍 stuff.

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  7. retweetou
    11 de nov

    “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” – Martin Fowler

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  8. retweetou
    9 de nov

    Hey , want to brush up on your tidyeval? Try this interactive tutorial covering symbols, quosures, !!, !!!, and more: (feedback welcome)

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  9. retweetou
    8 de nov

    Great advice from : if you want to get started with , use a dataset you’re interested in, not mtcare. One possibility - download your social media or gmail data!

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  10. retweetou
    5 de nov

    I'm starting monthly bite-size data posts on meta! 📊 Check out this first one about how users' actions are correlated.

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  11. retweetou
    4 de nov

    😻 Just saw 's work for the first time, and I'm so in love! 🖍 "Sketchplanations - A weekly explanation in a sketch"

    Mercator Projection
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  12. retweetou
    30 de out

    Find a typo somewhere in a bookdown book (e.g. ) or in a package readme/docs on github? You can propose the fix yourself! Follow this step-by-step tutorial w/ lots of screenshots . H/t & thank you to .

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  13. retweetou
    17 de out

    hey! I just gave a talk at on what I've discovered about while hosting , the podcast. Slides are here:

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  14. retweetou
    17 de out

    Great talk from yesterday on the benefits of coding your data analysis for reproducibility. Bonus: I’ve never related to a speaker more. “All code is collaborative even if it’s just between you and future you”

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  15. retweetou
    17 de out

    Just like reserving money for unforeseen costs when budgeting, you should set aside time for unforeseen delays when planning for a data science task. Reduces stress when something keeps failing without knowing why or you just don't see the answer right away.

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  16. retweetou
    12 de out

    Materials from my with are now available in this repo: , Includes code, deck and links to the published work.

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  17. 10 de out

    "All the right math and data to solve the wrong problem" - sharing that type III errors are at the heart of Decision Intelligence

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  18. 10 de out

    "Irrationality is an expensive bug" - I love this setup of human decision biases and how / can improve decision making by at

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  19. retweetou
    8 de out

    Just tinkering… 📊 "Pretty scatter plots w/ ggplot2" 📽 "Decouple Code and Output in xaringan"

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  20. retweetou
    5 de out

    Running the tests again without saving your changes

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  21. 7 de out

    ICYMI. How and when: ridge regression with glmnet Or, "When does Ridge🥊 OLS?" 🔗

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