
Offering accessible and nuanced coverage, Richard W. Hamming discusses theories of probability with unique clarity and depth. Topics covered include the basic philosophical assumptions, the nature of stochastic methods, and Shannon entropy. One of the best introductions to the topic, The Art of Probability is filled with unique insights and tricks worth knowing.
* Calculus by Spivak. This was used in my intro calculus course in university. It's very much a bottom-up, first-principles construction of calculus. Very proof-based, so you have to be into that. Tons of exercises, including some that sneakily introduce pretty advanced concepts not explicitly covered in the main text. This book, along with the course, rearranged by brain. Not sure how useful it would be for self-study though.
* Measurement by Lockhart. I haven't read the whole thing, but have enjoyed working through some of the exercises. A good book for really grokking geometric proofs and understanding "mathematical beauty", rather than just cranking through algebraic proofs step by step.
* Naive Set Theory by Halmos. Somewhat spare, but a nice, concise introduction to axiomatic set theory. Brings you from nothing up to the Continuum Hypothesis. I read this somewhere around my first year in university and it was another brain-rearranger.
In particular; Methods of Mathematics Applied to Calculus, Probability, and Statistics is one of a kind.
For the OP; there is also The Art Of Probability by Richard Hamming which you might find interesting.
And finally of course everybody needs to read; The Art of Doing Science and Engineering: Learning to Learn by Richard Hamming.
I own Spivak's Calculus (which is a great book), but if you are not interested in the pure math side or you just don't want to grind a 700 page tome I recommend Calculus made easy. Contrary to the title and the small size of this book, it's an amazing and intuitive. When I read Calculus Made Easy I also read Infinite powers by Steven Strogratz they complete each other very well.
I have a copy of "The Art of Probability: For Scientists and Engineers" by Hamming it's a really good book.
If you are interested in Bayesian probability, machine learning or information theory I recommend "Information Theory, Inference, and Learning Algorithms" by MacKay it's an amazing book. It's available as in PDF format on the author's website.
* Methods of Mathematics Applied to Calculus, Probability, and Statistics.
* The Art of Probability.