Uni resources
I'm currently studying a Bachelor of Science part-time at The University of Melbourne, majoring in maths and statistics with lots of computing electives. This page holds a collection of resources I've found useful in my subjects so far. Most of these were not recommended or prescribed by my lecturers, but happened to be really helpful as extra resources.
General
The maths is fun website is my go-to for explanations of basic concepts and rules that I've forgotten or don't quite understand. I used it a lot during my earlier calculus and linear algebra subjects, and I keep going back because the explanations are really clear and helpful.
How to Study for a Mathematics Degree by Lara Alcock was useful in thinking about how to approach maths subjects and adjust my study process. I've only read part of it, but I also got some value out of How to Think Like a Mathematician by Kevin Houston.
Calculus
I didn't use textbooks much for my calculus subjects, but Paul's online notes were really useful, as were the resources available from the mathcentre uk website.
Algorithms
Grokking Algorithms by Aditya Y. Bhargava was really useful when I took my second algorithms subject. I found it helped a lot with understanding graph algorithms and the knapsack problem.
In both my algorithms subjects we wrote code in C, and I relied a lot on Beej's Guide to C Programming by Brian "Beej Jorgensen" Hall.
Probability
Introduction to Probability by Blitzstein & Hwang was indispensable for this subject. It went a tiny bit further than my probability class and covered a touch of statistics (mainly order statistics), but I wish there was a second volume that covered all of my stats class, but I really liked the way this book explained things. I also really liked The Drunkard's Walk by Leonard Mlodinow for an informal, intuitive intro to probability and randomness.
Statistics
When I took Statistics, I relied a lot on Probability and Statistics for Computer Scientists by Michael Baron. The examples were all computing-related, but nothing requiring a deep knowledge of computing or programming, and otherwise it was just a well-written book that explained concepts in an approachable way. The 2nd edition is fine, but the 3rd edition has been updated to add R code examples as well as MATLAB, and I found that more useful since my lab classes used R.
These online notes were really useful during my statistics subject. They cover pretty much all the content in my subject, and the explanations and diagrams are approachable.
Real Analysis
This subject introduced reading and writing proofs, as well as analysis, so I found Proofs by Jay Cummings and Book of Proof by Richard Hammack useful for the proofs part.
For the actual analysis part of the subject, I liked Real Analysis by Jay Cummings, and How to Think about Analysis by Lara Alcock.