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I have been reading this book steadily recently and it has repaid my serious study. It is written in a very clever way, focusing on giving the big picture, while not neglecting considerations related to direct application. The concentration on analysis of illustrative examples really aids self-study. The author displays a brilliance in this book in presenting Matlab and interweaving it with the study of important topics in numerical mathematics. The emphasis is on the mathematics, understanding, and applying numerical methods, rather than strictly in technical details of Matlab. I recommend this book as a learning aid for Matlab, if one is interested in certain areas of numerical analysis that the book addresses. The first part of the book is pretty elementary, but the presentation is interesting and engaging, and aspires, to a certain extent, to serve as a nice survey introductory treatment at the high school and freshman college level of applied mathematics. There is a kind of juvenile cuteness about the first several chapters, but the level does start to pick up when differential equations are discussed. Applied mathematics is establishing itself, more and more, as a competitor for traditional pure mathematics, thanks to the power of modern computation. The problems the applied mathematicians work on are growing in significance and originality, due to the impact of improvements in computers and computational techniques. This is the "experimental" or "engineering" side, perhaps, of mathematics, and it can often be as exciting, clever and original as the "theoretical" or pure side of mathematics. My own feeling is that computational science (as we might call this area of mathematics now) hearkens back to the ancient Pythagoreans, and an interest in understanding and grasping the harmony of the cosmos.
In the latter portion of the book, much more advanced perspectives are discussed, and I think that the need for real dedicated and persistent effort on the part of the reader (more at the PhD level or a fairly unusually superior undergraduate level of applied mathematics) is needed. At least, I found this to be the case for myself. My background in physics and mathematics was helpful, but I still had to work pretty hard to understand satisfactorily this latter material. To my mind, the most advanced material in the book takes much effort to learn, for a typical American undergraduate student, and a fair background in PDEs, fluid physics, electrodynamics, and quantum mechanics at least at the senior level in physics seems almost a prerequisite for grasping the full extent of this book. Note that the intent of the book is not to transmit rigor and the pure math (albeit it comes with the effort you put in) but to grasp the engineering and applied math aspects, oriented toward physical intuition (which can often be extremely non-intuitive relative to more modern areas of physics). I don't think many undergraduate applied mathematics students will find the material in the latter part of the book that digestible: It seems mostly for grad students and PhD students in applied math intent on going into research. Nonetheless, it is a pretty fascinating journey, if not an easy one.
The last few chapters detail possible "real-world" student projects. I thought all of the projects sounded interesting, but I have not done the work needed to explore the problems posed, so this is very subjective on my part.
The book is panoramic and explores an exciting vista of the future for applied math applications in data science, engineering and applied math. It is a stunning achievement, and opens an exciting landscape for exploration. It has certainly been one of the best books I have ever read and reminds me a little of Feynman's wonderful three volume intro to physics in its breadth and the brilliance it displays.
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Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data
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Customers say
Customers find the textbook effective at making dry mathematical concepts accessible. Moreover, the book serves as a superior learning aid for Matlab, with one customer noting it helps bridge the gap between computer science and other fields.
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8 customers mention content, 7 positive, 1 negative
...The author did a terrific job in explaining the methods like POD, DMD. There is a short chapter on Finite element analysis too....Read more
Intuitive book and good reading. Not very rigorous but definitely helpful to new comers.Read more
...The emphasis is on the mathematics, understanding, and applying numerical methods, rather than strictly in technical details of Matlab....Read more
Excellent, detailed presentation of Singular Value Decomposition and other essentials of computational data science....Read more
5 customers mention learning aid, 5 positive, 0 negative
Great reference book. Totally recommend.Read more
...It has been tremendously helpful to have this book to go back and review material not thoroughly covered in class on MATLAB....Read more
This book really helped me span the bridge between computer science and higher math....Read more
I have been reading this book steadily recently and it has repaid my serious study....Read more
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- Amazon CustomerReviewed in the United Kingdom on January 9, 2016
This Book teaches you through 'Guided Discovery'
Format: PaperbackVerified Purchase - TarunReviewed in India on October 26, 2014
This is not book for beginner
Format: PaperbackVerified Purchase - A. PatelReviewed in the United Kingdom on July 25, 2020
Clear explanations ,easy to follow
Format: PaperbackVerified Purchase
