Lecture 3.2: Model Selection - Part 2

How do we evaluate whether machine learning models will work well in practice? In part 2 of this lecture, we'll discuss how to include real-world costs and preferences, calibrate models, analyze errors, and tune hyperparameters. Slides and notebooks: https://ml-course.github.io/master/