Modeling the Complexities of Machine Learning

This chapter explores the journey of academic modeling with a focus on practical applications like coding a Helmholtz machine. The dialogue addresses the challenges of visualizing complex algorithms, enhancing comprehension of in silico agents, and improving the representation of belief updates in machine learning contexts.