I was reading the answers and comments to this question: Why is Newton's method not widely used in machine learning?
and realised that I would like to learn a lot more about numerical optimization. I was especially interested to notice some quite divergent answers.
I see that the following book was recommended:
Nocedal, J., & Wright, S. (n.d.). Numerical optimization (Second edition.). Springer-Verlag. 2006. https://www.springer.com/us/book/9780387303031
However, my university library has only 1 copy and it is high demand.
I am looking for other books of a similar level, that would be particularly useful for applications in statistics and machine learning (not just deep learning, but including DL too)
[I have a BS in Physics and I'm currently on a doctoral programme in data science]