SIAM Review, Volume 62, Issue 4, Page 985-994, January 2020.
The first and featured review is on the book Introduction to Numerical Methods for Variational Problems, by Hans Petter Langtangen and Kent-Andre Mardal. It is one of the last books co-authored by Hans Petter Langtangen, who was a very influential, enthusiastic researcher and teacher, and nevertheless a very kind person. I met him several times during my time on the editorial board of SISC, where he used to be the editor-in-chief. The scientific community in the field of scientific computing owes a lot to him. The reviewer of the book, Akil Narayan, has written a very careful and diligent review on this book pointing out its nonstandard features, which let it stand out from the crowd and make it very worthwhile reading. The featured review is followed by Daniele Boffi's review on the book Convection-Diffusion Problems. An Introduction to Their Analysis and Numerical Solution, by Martin Stynes and David Stynes. Daniele recommends the book as a “concise and well-organized introduction to the approximation of convection-diffusion problems.” Among our reviews, we have three more books related to data science: Neural Networks and Statistical Learning, by Ke-Lin Du and M. N. S. Swamy, which is reviewed by Jan Pablo Burgard with the comment that the book “can be seen as a central reference point for the mathematical understanding and implementation of the core ideas of neuronal networks and statistical learning techniques''; John Harlim's Data-Driven Computational Methods: Parameter and Operator Estimations, very positively reviewed by Nikolas Kantas; and the book Mathematics for Machine Learning, by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Og. Finally, I would like to mention the book by Doug Arnold on Finite Element Exterior Calculus, which is reviewed by the expert Ralf Hiptmair, who praises the book as “a work bridging the divide sometimes separating what is labeled pure and applied mathematics.”

中文翻译：

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书评

SIAM评论，第62卷，第4期，第985-994页，2020年1月。
汉斯·皮特·朗坦根（Hans Petter Langtangen）和肯特·安德烈·马尔达尔（Kent-Andre Mardal）合着的《变分问题数值方法简介》一书是第一个具有特色的评论。这是汉斯·佩特·朗坦根（Hans Petter Langtangen）合着的最后一本书，汉斯·佩特·朗坦根（Hans Petter Langtangen）是一位很有影响力，热情洋溢的研究者和老师，但是却非常友善。在我担任SISC编辑委员会期间，我几次见过他，他曾是该委员会的总编辑。科学计算领域的科学界应归功于他。该书的审稿人Akil Narayan对这本书进行了非常仔细而勤奋的评论，指出其非标准功能，使其脱颖而出，非常值得一读。特色评论之后是Daniele Boffi对对流扩散问题的评论。Martin Stynes和David Stynes对其分析和数值解进行了介绍。Daniele推荐这本书为“对流扩散问题近似的简明扼要的介绍。” 在我们的评论中，我们还有三本与数据科学相关的书：《神经网络与统计学习》（由Ke-Lin Du和MNS Swamy撰写），由Jan Pablo Burgard进行了评论，并评论说“这本书可以被视为主要参考”对神经网络和统计学习技术的核心思想进行数学理解和实施的要点''; 约翰·哈利姆（John Harlim）的数据驱动计算方法：参数和算子估计，Nikolas Kantas对此进行了非常积极的评论。以及Marc Peter Deisenroth，A.Aldo Faisal和Cheng Soon Og所著的《机器学习数学》一书。