The Problem of Forgetting in Machine Learning

This chapter discusses the classical problem of forgetting in machine learning applications using the example of a model that identifies handwritten numbers. It emphasizes the importance of allowing the model to forget previous behaviors and try different approaches to continue learning beyond local maxima.