This advanced machine learning text is suitable for graduate students or highly motivated undergraduate studens in statistics, computer science, electrical engineering, and applied mathematics. The text is self-contained and only assumes knowledge of lower-division linear algebra and upper-division probability theory. Students, professional engineers, and multidisciplinary scientists possessing these minimal prerequisites will find this text challenging yet accessible.

The Learning Machines 101 podcast How to Become a Machine Learning Expert (https://www.learningmachines101.com/lm101-078-ch0-how-to-become-a-machine-learning-expert/) provides useful guidance regarding not only how to prepare for reading this text but also more general guidance for newcomers to the field regarding how to develop expertise in the area of machine learning.