Flexible feature engineering using {recipes}

This was a talk given for internal AstraZeneca conference.

Tidy Text Tutorial

2 hour tutorial, 1 part text mining, 1 part modeling with text. https://github.com/socalrug/hackathon-2023-04

Having a purrr-tastic time

This was a small talk about purrr in general and some of the new things that was included in the 1.0.0 release.

tidyclust - expanding tidymodels to clustering

Accepted talk at rstudio::conf(2022) This talk marks the grand introduction of tidyclust, a new package that provides a tidy unified interface to clustering model within the tidymodels framework. While tidymodels has been a leap forward in making machine learning methods accessible to a general audience in R, it is currently limited to the realm of supervised learning. tidyclust, by Emil Hvitfeldt and Kelly Bodwin, builds upon the interfaces familiar to tidymodels users to make unsupervised clustering models equally approachable.

Improvements in text preprocessing using textrecipes

Accepted talk at useR2022! Text constitutes an ever-growing part of the data available to us today. However, it is a non-trivial task to transform text, represented as long strings of characters, into numbers that we can use in our statistical and machine learning models. textrecipes has been around for a couple of years to aid the practitioner in transforming text data into a format that is suitable for machine learning models.

Machine learning with {tidymodels}

Accepted workshop at useR2022! This workshop will provide a gentle introduction to machine learning with R using the modern suite of predictive modeling packages called tidymodels. We will build, evaluate, compare, and tune predictive models. Along the way, we’ll learn about key concepts in machine learning including overfitting, the holdout method, the bias-variance trade-off, ensembling, cross-validation, and feature engineering. Learners will gain knowledge about good predictive modeling practices, as well as hands-on experience using tidymodels packages like parsnip, rsample, recipes, yardstick, and tune.