Incidentally, my college calculus class also used Stewart.
My philosophy with textbooks was to buy only ones I felt I'd go back to after uni - basic references in each major field I studied - and this was reasonable for me for calculus. My only regret was shelling out for new copies because I was young and stupid and thought I needed them right now for the class, before I knew better. You can certainly pick up cheap second-hand copies per the parent post.
I also used Kreyzig too but found that to be a bit harder to learn from, albeit more in depth.
I learned from the Stewart book and it's not terrible, but I don't think that is a very good book for self learning. How to ace calculus or the calculus lifesaver, plus a book with solved examples is probably better for self study.
And some linear algebra book by Strang (as others have said.) I don't remember which one I learned from, but I do remember it was excellent.
I can't recommend a good stats/probability book. People recommend Statistical Inference by Casella and Berger, although I wasn't super impressed with it.
You'll also want a good understanding of set theory and proof writing. I don't remember what book I learned from, but try to find some introduction to math thought.
This is all assuming you have a good understanding of algebra. The above mentioned books require geometry/trig, but you don't actually need that for machine learning.