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
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.
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.
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.
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.
Artists who are women are underrepresented in art history textbooks, and we can use resampling to robustly understand more about this imbalance.continue reading.
Will squirrels will come eat from your bird feeder? Let’s fit a model both with and without downsampling to find out.continue reading.
Learn how to handle predictors with high cardinality using tidymodels for accreditation data on UK museums.continue reading.
New functionality in tidytext supports identifying high FREX and high lift words from topic modeling results.continue reading.
Learn how to use vetiver to set up different types of prediction endpoints for your deployed model.continue reading.
After you train a model, you can use vetiver to prepare a Dockerfile and deploy your model in a flexible way.continue reading.
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.
Use summarization, a single linear model, and bootstrapping to understand what economic activities involve a larger pay gap for women.continue reading.
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.
Understand how much money colleges spend on sports using linear modeling and bootstrap intervals.continue reading.
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.
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.