Mathematical foundations of machine learning edition

This thread is dedicated to the mathematical aspects of computation. It doesn't matter whether or not it's theoretical CS or applied. Old thread here: >>12893521

This thread features quantum algorithms. Quantum computing is a *huge* field (quantum algos alone is huge), and you can talk about any part of it here, but today we will be focusing on the algorithmic aspects. If there is a demand for quantum *hardware* (the electrical engineering and physics), I will be happy to provide resources!

Here are some resources for beginners:
https://teachyourselfcs.com/

Free books:
https://z-lib.org/
http://gen.lib.rus.ec/
https://spoon.wiki/Books

Here are some resources to get you started.

Linear Algebra by Hoffman and Kunze:
https://www.cin.ufpe.br/~jrsl/Books/Linear%20Algebra%20-%20Kenneth%20Hoffman%20&%20Ray%20Kunze%20.pdf
Don’t need to know everything but it’s the bread butter. Of course calculus, combinatorics, the basics of abstract algebra, etc. show up too, but linear algebra is the most important thing to be comfortable with *at first.*

Quantum Computation and Quantum Information by Isaac Chuang and Michael Nielsen (the “Mike’n’Ike" book):
http://mmrc.amss.cas.cn/tlb/201702/W020170224608149940643.pdf
Great intro book for quantum computing. Chapters 2-3 (~100 pages) is enough background. Chapter 6 is a good intro to quantum searching. Go wild with this book - it's really good for many aspects of quantum computing!

Lecture Notes on Quantum Algorithms (completely free, by Andrew Childs, top researcher):
http://www.cs.umd.edu/~amchilds/qa/
Has links to various webpages with assignments!