Resampling to understand gender in #TidyTuesday art history data
Artists who are women are underrepresented in art history textbooks, and we can use resampling to robustly understand more about this imbalance.continue reading.
Author: Blog on Julia Silge
To downsample imbalanced data or not, with #TidyTuesday bird feeders
Will squirrels will come eat from your bird feeder? Let’s fit a model both with and without downsampling to find out.continue reading.
High cardinality predictors for #TidyTuesday museums in the UK
Learn how to handle predictors with high cardinality using tidymodels for accreditation data on UK museums.continue reading.
Delete all your tweets using rtweet
Worried about how a certain social media platform is going and want to start removing yourself? Learn how to delete all your tweets.continue reading.
Find high FREX and high lift words for #TidyTuesday Stranger Things dialogue
New functionality in tidytext supports identifying high FREX and high lift words from topic modeling results.continue reading.
Predict the status of #TidyTuesday Bigfoot sightings
Learn how to use vetiver to set up different types of prediction endpoints for your deployed model.continue reading.
Use Docker to deploy a model for #TidyTuesday LEGO sets
After you train a model, you can use vetiver to prepare a Dockerfile and deploy your model in a flexible way.continue reading.
Sliding windows for #TidyTuesday rents in San Francisco
The slider package provides support for flexible sliding window aggregation, and we can use these kinds of sliding windows to analyze rents over time.continue reading.
Three ways to look at #TidyTuesday UK pay gap data
Use summarization, a single linear model, and bootstrapping to understand what economic activities involve a larger pay gap for women.continue reading.
Use resampling to understand #TidyTuesday drought in TX
The spatialsample package is gaining many new methods this summer, and we can use spatially aware resampling to understand how drought is related to other quantities across Texas.continue reading.
Predict #TidyTuesday NYT bestsellers
Will a book be on the NYT bestseller list a long time, or a short time? We walk through how to use wordpiece tokenization for the author names, and how...continue reading.
Handling model coefficients for #TidyTuesday collegiate sports
Understand how much money colleges spend on sports using linear modeling and bootstrap intervals.continue reading.
Poisson regression for #TidyTuesday counts of R package vignettes
The tidymodels framework provides extension packages for specialized tasks such as Poisson regression. Learn how to fit a zero-inflated model for understanding how R package releases are related to number...continue reading.
Inference for #TidyTuesday aircraft and rank of Tuskegee airmen
The infer package is part of tidymodels and provides an expressive statistical grammar. Understand how to use infer, and celebrate Black History Month by learning more about the Tuskegee airmen.continue reading.
Predict ratings for #TidyTuesday board games
Use custom feature engineering for board game categories, tune an xgboost model with racing methods, and use explainability methods for deeper understanding.continue reading.
Text predictors for #TidyTuesday chocolate ratings
Get started with feature engineering for text data, transforming text to be used in machine learning algorithms.continue reading.
Topic modeling for #TidyTuesday Spice Girls lyrics
Learn how to train, explore, and understand an unsupervised topic model for text data.continue reading.
Predicting viewership for #TidyTuesday Doctor Who episodes
Using a tidymodels workflow can make many modeling tasks more convenient, but sometimes you want more flexibility and control of how to handle your modeling objects. Learn how to handle...continue reading.
Spatial resampling for #TidyTuesday and the #30DayMapChallenge
Use spatial resampling to more accurately estimate model performance for geographic data.continue reading.
Predict #TidyTuesday giant pumpkin weights with workflowsets
Get started with tidymodels workflowsets to handle and evaluate multiple preprocessing and modeling approaches simultaneously, using pumpkin competitions.continue reading.
