56,966 blogs · [ { "id": "01a08792-443f-7249-a3f0-840908321485", "title": "Use Positron Assistant with GitHub Copilot", "url": "https://juliasilge.com/blog/copilot-african-languages/", "published_at": "2026-01-20T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840908e34803", "title": "Explore #TidyTuesday literary prizes with Positron’s Data Explorer", "url": "https://juliasilge.com/blog/literary-prizes/", "published_at": "2025-10-13T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840909a083d5", "title": "Release an R package with Positron", "url": "https://juliasilge.com/blog/r-pkg-release/", "published_at": "2025-03-19T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-84090a727e92", "title": "Positron in action with #TidyTuesday orca encounters", "url": "https://juliasilge.com/blog/orcas-positron/", "published_at": "2024-10-14T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-84090b5f56c8", "title": "Educational attainment in #TidyTuesday UK towns", "url": 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tidymodels and #TidyTuesday cocktail recipes", "url": "https://juliasilge.com/blog/cocktail-recipes-umap/", "published_at": "2020-05-27T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840930437e7c", "title": "tidylo is now on CRAN! 🎉", "url": "https://juliasilge.com/blog/tidylo-cran/", "published_at": "2020-05-26T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-8409304d7bd5", "title": "Tune XGBoost with tidymodels and #TidyTuesday beach volleyball", "url": "https://juliasilge.com/blog/xgboost-tune-volleyball/", "published_at": "2020-05-21T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-8409308d2c3d", "title": "Learn tidymodels with my supervised machine learning course", "url": "https://juliasilge.com/blog/tidymodels-ml-course/", "published_at": "2020-05-15T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-8409312a7b4d", "title": "Multinomial classification with tidymodels and #TidyTuesday volcano eruptions", "url": "https://juliasilge.com/blog/multinomial-volcano-eruptions/", "published_at": "2020-05-13T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840931ecf181", "title": "Sentiment analysis with tidymodels and #TidyTuesday Animal Crossing reviews", "url": "https://juliasilge.com/blog/animal-crossing/", "published_at": "2020-05-06T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-8409324274e5", "title": "Modeling #TidyTuesday GDPR violations with tidymodels", "url": "https://juliasilge.com/blog/gdpr-violations/", "published_at": "2020-04-22T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840932c2c538", "title": "PCA and the #TidyTuesday best hip hop songs ever", "url": "https://juliasilge.com/blog/best-hip-hop/", "published_at": "2020-04-14T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-8409336e0828", "title": "Bootstrap resampling with #TidyTuesday beer production data", "url": "https://juliasilge.com/blog/beer-production/", "published_at": "2020-04-02T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840933e2d905", "title": "Tuning random forest hyperparameters with #TidyTuesday trees data", "url": "https://juliasilge.com/blog/sf-trees-random-tuning/", "published_at": "2020-03-26T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840934b524b8", "title": "LASSO regression using tidymodels and #TidyTuesday data for The Office", "url": "https://juliasilge.com/blog/lasso-the-office/", "published_at": "2020-03-17T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840934f16409", "title": "Preprocessing and resampling using #TidyTuesday college data", "url": "https://juliasilge.com/blog/tuition-resampling/", "published_at": "2020-03-10T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840935196054", "title": "Hyperparameter tuning and #TidyTuesday food consumption", "url": "https://juliasilge.com/blog/food-hyperparameter-tune/", "published_at": "2020-02-18T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-8409356db844", "title": "#TidyTuesday hotel bookings and recipes", "url": "https://juliasilge.com/blog/hotels-recipes/", "published_at": "2020-02-11T00:00:00+00:00" }, { "id": "01a08792-443f-7249-a3f0-840935fd7801", "title": "#TidyTuesday and tidymodels", "url": "https://juliasilge.com/blog/intro-tidymodels/", "published_at": "2020-02-05T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29d0ee1ac", "title": "Modeling salary and gender in the tech industry", "url": "https://juliasilge.com/blog/salary-gender/", "published_at": "2019-12-31T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29d43734a", "title": "Opioid prescribing habits in Texas", "url": "https://juliasilge.com/blog/texas-opioids/", "published_at": "2019-10-12T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29db457c7", "title": "(Re)Launching my supervised machine learning course", "url": "https://juliasilge.com/blog/supervised-ml-course/", "published_at": "2019-09-23T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29dbedcac", "title": "Practice using lubridate... THEATRICALLY", "url": "https://juliasilge.com/blog/lubridate-london-stage/", "published_at": "2019-08-26T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29eadc065", "title": "Introducing tidylo", "url": "https://juliasilge.com/blog/introducing-tidylo/", "published_at": "2019-07-08T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29eb23860", "title": "Reordering and facetting for ggplot2", "url": "https://juliasilge.com/blog/reorder-within/", "published_at": "2019-07-01T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c29f769987", "title": "Fixing your mistakes: sentiment analysis edition", "url": "https://juliasilge.com/blog/sentiment-lexicons/", "published_at": "2019-06-14T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c2a04e9429", "title": "Relaunching the qualtRics package", "url": "https://juliasilge.com/blog/qualtrics-relaunch/", "published_at": "2019-04-30T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c2a06e040f", "title": "Writing a letter to DataCamp", "url": "https://juliasilge.com/blog/datacamp-misconduct/", "published_at": "2019-04-16T00:00:00+00:00" }, { "id": "01a08792-4440-732d-bf0c-86c2a1663a0a", "title": "Read all about it! Navigating the R Package Universe", "url": "https://juliasilge.com/blog/r-journal-navigating/", "published_at": "2019-02-24T00:00:00+00:00" } ] posts Claim your blog

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2026

Use Positron Assistant with GitHub Copilot original ↗

20 Jan 2026

2025

Explore #TidyTuesday literary prizes with Positron’s Data Explorer original ↗

13 Oct 2025

Release an R package with Positron original ↗

19 Mar 2025

2024

Positron in action with #TidyTuesday orca encounters original ↗

14 Oct 2024

Educational attainment in #TidyTuesday UK towns original ↗

24 Apr 2024

Changes in #TidyTuesday US polling places original ↗

17 Jan 2024

2023

Empirical Bayes for #TidyTuesday Doctor Who episodes original ↗

29 Nov 2023

Logistic regression modeling for #TidyTuesday US House Elections original ↗

7 Nov 2023

Topic modeling for #TidyTuesday Taylor Swift lyrics original ↗

23 Oct 2023

Where are #TidyTuesday haunted cemeteries compared to haunted schools?original ↗

11 Oct 2023

How often does Roy Kent say "F*CK"?original ↗

27 Sept 2023

Evaluate multiple modeling approaches for #TidyTuesday spam email original ↗

1 Sept 2023

Classification metrics for #TidyTuesday GPT detectors original ↗

19 Jul 2023

What tokens are used more vs. less in #TidyTuesday place names?original ↗

5 Jul 2023

Predict the magnitude of #TidyTuesday tornadoes with effect encoding and xgboost original ↗

20 May 2023

Tune an xgboost model with early stopping and #TidyTuesday childcare costs original ↗

11 May 2023

Deploy a model on AWS SageMaker with vetiver original ↗

4 May 2023

Use OpenAI text embeddings with #TidyTuesday horror movie descriptions original ↗

5 Apr 2023

Resampling to understand gender in #TidyTuesday art history data original ↗

8 Feb 2023

To downsample imbalanced data or not, with #TidyTuesday bird feeders original ↗

18 Jan 2023

2022

High cardinality predictors for #TidyTuesday museums in the UK original ↗

25 Nov 2022

Delete all your tweets using rtweet original ↗

10 Nov 2022

Find high FREX and high lift words for #TidyTuesday Stranger Things dialogue original ↗

20 Oct 2022

Predict the status of #TidyTuesday Bigfoot sightings original ↗

23 Sept 2022

Use Docker to deploy a model for #TidyTuesday LEGO sets original ↗

8 Sept 2022

Sliding windows for #TidyTuesday rents in San Francisco original ↗

4 Aug 2022

Three ways to look at #TidyTuesday UK pay gap data original ↗

30 Jun 2022

Use resampling to understand #TidyTuesday drought in TX original ↗

15 Jun 2022

Predict #TidyTuesday NYT bestsellers original ↗

11 May 2022

Handling model coefficients for #TidyTuesday collegiate sports original ↗

9 Apr 2022

Poisson regression for #TidyTuesday counts of R package vignettes original ↗

16 Mar 2022

Inference for #TidyTuesday aircraft and rank of Tuskegee airmen original ↗

11 Feb 2022

Predict ratings for #TidyTuesday board games original ↗

28 Jan 2022

Text predictors for #TidyTuesday chocolate ratings original ↗

21 Jan 2022

2021

Topic modeling for #TidyTuesday Spice Girls lyrics original ↗

15 Dec 2021

Predicting viewership for #TidyTuesday Doctor Who episodes original ↗

27 Nov 2021

Spatial resampling for #TidyTuesday and the #30DayMapChallenge original ↗

5 Nov 2021

Predict #TidyTuesday giant pumpkin weights with workflowsets original ↗

22 Oct 2021

Multiclass predictive modeling for #TidyTuesday NBER papers original ↗

29 Sept 2021

Dimensionality reduction for #TidyTuesday Billboard Top 100 songs original ↗

15 Sept 2021

Fit and predict with tidymodels for #TidyTuesday bird baths in Australia original ↗

1 Sept 2021

Modeling human/computer interactions on Star Trek from #TidyTuesday with workflowsets original ↗

24 Aug 2021

Predict housing prices in Austin TX with tidymodels and xgboost original ↗

15 Aug 2021

Supervised Machine Learning for Text Analysis in R is now complete original ↗

13 Aug 2021

Tune xgboost models with early stopping to predict shelter animal status original ↗

7 Aug 2021

Use racing methods to tune xgboost models and predict home runs original ↗

29 Jul 2021

Predict which #TidyTuesday Scooby Doo monsters are REAL with a tuned decision tree model original ↗

13 Jul 2021

Create a custom metric with tidymodels and NYC Airbnb prices original ↗

30 Jun 2021

Class imbalance and classification metrics with aircraft wildlife strikes original ↗

21 Jun 2021

Partial dependence plots with tidymodels and DALEX for #TidyTuesday Mario Kart world records original ↗

28 May 2021

Predict availability in #TidyTuesday water sources with random forest models original ↗

6 May 2021

Estimate change in #TidyTuesday CEO departures with bootstrap resampling original ↗

28 Apr 2021

Which #TidyTuesday Netflix titles are movies and which are TV shows?original ↗

23 Apr 2021

Which #TidyTuesday post offices are in Hawaii?original ↗

14 Apr 2021

Dimensionality reduction of #TidyTuesday United Nations voting patterns original ↗

24 Mar 2021

Bootstrap confidence intervals for #TidyTuesday Super Bowl commercials original ↗

4 Mar 2021

Getting started with k-means and #TidyTuesday employment status original ↗

24 Feb 2021

Understand your models with #TidyTuesday inequality in student debt original ↗

12 Feb 2021

Learn tidytext with my new learnr course original ↗

2 Feb 2021

Explore art media over time in the #TidyTuesday Tate collection dataset original ↗

15 Jan 2021

Predicting injuries for Chicago traffic crashes original ↗

4 Jan 2021

2020

Upcoming changes to tidytext: threat of COLLAPSE original ↗

16 Dec 2020

Tune random forests for #TidyTuesday IKEA prices original ↗

3 Dec 2020

Tune and interpret decision trees for #TidyTuesday wind turbines original ↗

29 Oct 2020

Predicting class membership for the #TidyTuesday Datasaurus Dozen original ↗

14 Oct 2020

Modeling #TidyTuesday NCAA women's basketball tournament seeds original ↗

7 Oct 2020

Handle class imbalance in #TidyTuesday climbing expedition data with tidymodels original ↗

23 Sept 2020

Introducing our new book, Tidy Modeling with R original ↗

17 Sept 2020

Train and analyze many models for #TidyTuesday crop yields original ↗

2 Sept 2020

Build a #TidyTuesday predictive text model for The Last Airbender original ↗

11 Aug 2020

Get started with tidymodels and #TidyTuesday Palmer penguins original ↗

28 Jul 2020

Supervised Machine Learning for Text Analysis in R original ↗

24 Jul 2020

Bagging with tidymodels and #TidyTuesday astronaut missions original ↗

15 Jul 2020

The Bechdel test and the X-Mansion with tidymodels and #TidyTuesday original ↗

30 Jun 2020

Impute missing data for #TidyTuesday voyages of captive Africans with tidymodels original ↗

17 Jun 2020

PCA and UMAP with tidymodels and #TidyTuesday cocktail recipes original ↗

27 May 2020

tidylo is now on CRAN! 🎉original ↗

26 May 2020

Tune XGBoost with tidymodels and #TidyTuesday beach volleyball original ↗

21 May 2020

Learn tidymodels with my supervised machine learning course original ↗

15 May 2020

Multinomial classification with tidymodels and #TidyTuesday volcano eruptions original ↗

13 May 2020

Sentiment analysis with tidymodels and #TidyTuesday Animal Crossing reviews original ↗

6 May 2020

Modeling #TidyTuesday GDPR violations with tidymodels original ↗

22 Apr 2020

PCA and the #TidyTuesday best hip hop songs ever original ↗

14 Apr 2020

Bootstrap resampling with #TidyTuesday beer production data original ↗

2 Apr 2020

Tuning random forest hyperparameters with #TidyTuesday trees data original ↗

26 Mar 2020

LASSO regression using tidymodels and #TidyTuesday data for The Office original ↗

17 Mar 2020

Preprocessing and resampling using #TidyTuesday college data original ↗

10 Mar 2020

Hyperparameter tuning and #TidyTuesday food consumption original ↗

18 Feb 2020

#TidyTuesday hotel bookings and recipes original ↗

11 Feb 2020

#TidyTuesday and tidymodels original ↗

5 Feb 2020

2019

Modeling salary and gender in the tech industry original ↗

31 Dec 2019

Opioid prescribing habits in Texas original ↗

12 Oct 2019

(Re)Launching my supervised machine learning course original ↗

23 Sept 2019

Practice using lubridate... THEATRICALLY original ↗

26 Aug 2019

Introducing tidylo original ↗

8 Jul 2019

Reordering and facetting for ggplot2 original ↗

1 Jul 2019

Fixing your mistakes: sentiment analysis edition original ↗

14 Jun 2019

Relaunching the qualtRics package original ↗

30 Apr 2019

Writing a letter to DataCamp original ↗

16 Apr 2019

Read all about it! Navigating the R Package Universe original ↗

24 Feb 2019