Julia Silge's Blog, page 2

Classification metrics for #TidyTuesday GPT detectors

Learn about different kinds of metrics for evaluating classification models, and how to compute, compare, and visualize them.

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.

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.

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.

Deploy a model on AWS SageMaker with vetiver

Learn how to train and deploy a model with R and vetiver on AWS SageMaker infrastructure.

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.

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.

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.

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.

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.