Description: The tidymodels framework is a collection of packages for modeling and machine learning using tidyverse principles. In this meetup, we will walk through a case study from SLICED (the competitive data science streaming show) on predicting Airbnb prices in NYC, and use hands-on live coding to learn how to use tidymodels to tune xgboost models. Come with your questions as we interactively code together and learn about topics like regression modeling, resampling, and model evaluation!
Bio: 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 practice. Julia loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.