Title: Three reasons to use tidymodels
Abstract: 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](www.tidymodels...) collection of packages offers a consistent, flexible framework for your modeling and machine learning work to address these problems. In this talk, we'll focus on three specific reasons to consider using tidymodels. We will start with model characteristics themselves, move to the wise management of your data budget, and finish with feature engineering.
**Speaker**: Julia Silge
Julia is a data scientist and software engineer at [RStudio PBC](rstudio.com/) where she works on open source modeling tools. She is both an international keynote speaker and a real-world practitioner focusing on data analysis and machine learning practice, and is the author of [Text Mining with R](www.tidytextmi...) with her coauthor David Robinson. She loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.
**Code of Conduct**: github.com/laR...
*Schedule*
6:30 open zoom
6:40-7:50 Presentation
~8:15 Virtual Social
*LA R Users Group*
Invite yourself to our Slack group: socalrug.herok...
Ask us any questions by email: larusers@gmail.com
Find our previous talks on GitHub: github.com/laR...
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Check out more events: laocr.org/
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Reach out if you want to be our speaker. First-time speakers are welcome
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