Below are digital resources that complement the book Practical Machine Learning with R: Tutorials and Case Studies.
A video from StatQuest by Josh Starmer. The video explains Logistic Regression in a fundamental and intuitive way.
A video from StatQuest by Josh Starmer. The video explains the difference between probabilities and odds. It also provides intuition for log-odds.
An article by Joos Korstanje in Towards Data Science. The article introduces the problem of unbalanced data and explains undersampling, oversampling, as well as SMOTE. Although the examples are programmed in Python, they are easy to understand.
This article in The Researchers’ Guide by Rahul Raoniar provides a step-by-step tutorial to predict diabetes using Logistic Regression together with the tidymodels library. It is based on a real-world diabetes dataset.