At the end of 2019, I posted a book list for engineers new to machine learning, to help develop basic knowledge of the fundamentals, organised into four groups: Machine Learning & Algorithms, Tools & Frameworks, Data Science & Analysis, and Companion Mathematics. This post provides an updated book list using the same groups, which have held up well. At the time the list covered 26 books, this iteration is more concise, covering 11 books. This time around 3 are new, and 3 have seen updated editions in the interim.