Exploring Resilient Machine Learning with a Focus on Defaults and Fallbacks

The chapter delves into the concepts of defaults and fallbacks as strategies for building resilient machine learning systems. Defaults involve training models to make predictions even with missing features, while fallbacks suggest using multiple models to ensure predictions can still be made under different conditions.