This book has two problems: - It's a collection of numerical algorithms and their implementations, not a systematic study of it. Meaning the style is "if you w

This book has two problems: - It's a collection of numerical algorithms and their implementations, not a systematic study of it. Meaning the style is "if you wish to do this, you use that" and so on. - It developed a bad reputation in the 1990s for the authors disallowing use of the implementations in the book without some kind of contract or permission. I'm not sure if the authors still do that but if you use any of the implementations from the book, you would always be concerned. A book (not the only one but one that I learned from) that solves both problems is Scientific Computing by Heath (https://amzn.com/0072399104 https://amzn.com/0072399104). (Well it doesn't provide implementations in any programming language, but if you understand the algorithms you should be able to implement them yourself). Finally, I would like to say that numerical-algorithms is the bigger of the two main areas of algorithms (the other being, what I call, combinatorial algorithms), and not only that, it's extremely relevant today for computer scientists in a world where the trend is to go from traditional programming to data science and machine learning. (I'm of the belief that CS departments and book-authors of the world have fooled their students for decades by teaching them only combinatorial algorithms (CLRS, Knuth, Skiena, that sort of stuff), and calling the class "Algorithms". This is a big reason CS students today have difficulty getting into machine learning theory, and CG theory, unless they go to grad school).