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Max Kuhn - Equivocals in Predictive Modeling
Max Kuhn - The Post-Modeling Model to Fix the Model
Max Kuhn - Comparing Posteriors: Estimating Practical Differences Between Models
Max Kuhn presents Rules, Rules, Rules! From Trees to Rules in Machine Learning
Max Kuhn Interviewed by DataScience.LA at useR
Max Kuhn is a software engineer and author
I Don't Want to Be a Dummy! Encoding Predictors for Trees
Formulas and Recipes by Max Kuhn
TidyTuesday: Model Evaluation using TidyModels and TidyPosterior
Tidy Modeling with R: When Should You Trust Your Predictions? (tmwr05 19)
Conformal Inference with Tidymodels - posit::conf(2023)
When Should You Trust Your Predictions? (tmwr04 19)
