Classification metrics for #TidyTuesday GPT detectors
Learn about different kinds of metrics for evaluating classification models, and how to compute, compare, and visualize them.continue reading.
Author: Blog on Julia Silge
What tokens are used more vs. less in #TidyTuesday place names?
Let’s use byte pair encoding tokenization along with Poisson regression to understand which tokens are more more often (or less often) in US place names.continue reading.
Predict the magnitude of #TidyTuesday tornadoes with effect encoding and xgboost
How well can we predict the magnitude of tornadoes in the US? Let’s use xgboost along with effect encoding to fit our model.continue reading.
Tune an xgboost model with early stopping and #TidyTuesday childcare costs
Can we predict childcare costs in the US using an xgboost model? In this blog post, learn how to use early stopping for hyperparameter tuning.continue reading.
Deploy a model on AWS SageMaker with vetiver
Learn how to train and deploy a model with R and vetiver on AWS SageMaker infrastructure.continue reading.
Use OpenAI text embeddings with #TidyTuesday horror movie descriptions
High quality text embeddings are becoming more available from companies like OpenAI. Learn how to obtain them and then use them for text analysis.continue reading.
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.
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.
