Three reasons to use tidymodels

Modeling and machine learning in R involve a bewildering array of heterogeneous packages, and establishing good statistical practice is challenging in any language. The tidymodels collection of packages offers a consistent, flexible framework for your modeling and machine learning work to address these problems. In this talk, speaker Julia Silge will focus on three specific reasons to consider using tidymodels. She will start with model characteristics themselves, move to the wise management of your data budget, and finish with feature engineering.

Check out tidymodels here: https://www.tidymodels.org/

About the speaker
Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open-source modeling tools. She is an author, an international keynote speaker, and a real-world practitioner focusing on data analysis and machine learning. Julia loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.

Website: https://juliasilge.com/
Twitter: https://twitter.com/juliasilge

Registration
Fill out this Google Form to register, and you'll receive the Zoom link by email: https://forms.gle/GiuFfHmGv8fy2Eph9