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Focusing on numerical computing, this textbook serves as an essential resource for science and engineering applications. It covers introductory topics along with advanced methods like optimization and regression using singular value decomposition. Emphasizing problem-solving, it features numerous exercises related to real-world applications. The text also delves into the mathematical theories behind the methods, highlighting their impact on computational accuracy. Additionally, computational examples are supported by code available on GitHub, with this edition catering to upper-division computational linear algebra courses.
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Introduction to Scientific Computing and Data Analysis, Mark H. Holmes
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- 2023
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