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.

I Did Advent of Code and This is What I Learned

Invited talk at NYR conference Many of us like puzzles. Wrestling with simple-to-understand questions, with trickly-to-find-solutions gives you a special type of bliss when you finally crack it. “Advent of Code” has been going for 7 years, challenging over 200,000 people with 25 days of action-packed programming puzzles. Participating in these events has taught me a lot about myself, my motivations, and my tool of choice, R. This talk will pull back the curtain on a collective journey of learning.