Books about the "Science" in Data Science? What are the books about the science and mathematics behind data science? It feels like so many "data science" books are programming tutorials and don't touch things like data generating processes and statistical inference. I can already code, what I am weak on is the math/stats/theory behind what I am doing.

If I am ready to burn $1000 on books (so around 10 books... sigh), what could I buy?

Examples: Agresti's Categorical Data Analysis, Linear Mixed Models for Longitudinal Data, etc... etc...
Introductory:


Machine Learning: The Art and Science of Algorithms that Make Sense of Data (Flach)
Learning From Data (Abu-Mostafa et al.)
Introduction to Statistical Learning (James et al.)


Digging deeper:


Elements of Statistical Learning (Hastie et al.)
Pattern Recognition and Machine Learning (Bishop)


Some special interest examples:


Convex Optimization (Boyd)
Bayesian Reasoning and Machine Learning (Barber)
Probabilistic Graphical Models (Koller)
Neural Networks for Pattern Recognition (Bishop)


Broader reference works on machine learning (not really what you asked for, but for completeness):


Machine Learning: A Probabilistic Perspective (Murphy)
Artificial Intelligence: A Modern Approach (Russell &amp; Norvig)


Bonus paper:


Statistical Modeling: The Two Cultures (Breiman)