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Wednesday, July 27 • 9:00am - 10:30am
Good practices for applied machine learning - from model development to model deployment

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The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles. Whether you are just starting out today or have years of experience with ML, tidymodels offers a consistent, flexible framework for your work. In this talk, learn how tidymodels has been designed to promote ergonomic, effective, and safe modeling practice. We will discuss how to think about the steps of building a model from beginning to end, how to fluently use different modeling and feature engineering approaches, how to avoid common pitfalls of modeling like overfitting and data leakage, and how to version and deploy reliable models trained in R.

avatar for Max Kuhn

Max Kuhn

RStudio, PBC
Max Kuhn is a software engineer at RStudio. He is currently working on improving R’s modeling capabilities. He was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years... Read More →
avatar for Julia Silge

Julia Silge

RStudio, PBC
Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open source tools for machine learning and MLOps. She holds a PhD in astrophysics and has worked as a data scientist in tech and the nonprofit sector, as well as a technical advisory committee... Read More →

Wednesday July 27, 2022 9:00am - 10:30am EDT
0. Potomac A+B