David C. Lay 在美国加利福尼亚大学获得硕士和博士学位。他是马里兰大学帕克学院数学系教授,同时还是阿姆斯特丹大学、阿姆斯特丹自由大学和德国凯泽斯劳滕大学的访问教授。Lay教授是“线性代数课程研究小组”的核心成员,发表了30多篇关于泛函分析和线性代数方面的论文,并与他人合著有多部数学教材。
Linear algebra is relatively easy for students during the early stages of the course, when the material is presented in a familiar, concrete setting. But when abstract concepts are introduced, students often hit a brick wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations), are not easily understood, and require time to assimilate. Since they are fundamental to the study of linear algebra, students' understanding of these concepts is vital to their mastery of the subject. Lay introduces these concepts early in a familiar, concrete Rn setting, develops them gradually, and returns to them again and again throughout the text. Finally, when discussed in the abstract, these concepts are more accessible. It includes easily identifiable Matlab icons in the margins next to Matlab examples and exercises and a CD-Rom bound in the back of the book includes additional Matlab exercises and programs. Instructor's Edition now includes selected solutions and MyMathLab. In this book fundamental ideas of linear algebra are introduced within the first seven lectures, in the concrete setting of Rn, and then gradually examined from different points of view. Later generalizations of these concepts appear as natural extensions of familiar ideas. The focus is on visualization of concepts throughout the book and it has icons in the margins to flag topics for which expanded or enhanced material is available on the Web; a modern view of matrix multiplication is presented. Definitions and proofs focus on the columns of a matrix rather than on the matrix entries; Numerical Notes give a realistic flavor to the text. Students are reminded frequently of issues that arise in the real-life use of linear algebra; and each major concept in the course is given a geometric interpretation because many students learn better when they can visualize an idea.
PCA这么重要的东西应该与SVD一样专门写一段,而不是放在“7.5 图像处理和统计学中的应用”底下当成普通例子来写。虽然这里PCA写的是真清晰真透彻,秒杀网上无数介绍。另外,SVD讲的太简略了,看完公式也抓不住本质。最好加入几何理解角度,并谈谈与PCA的异同。
评分A first course in linear algebra is dramatically different from most mathematics courses that precede it.The focus shifts from learning computational procedures to digesting and mastering basic concepts that underlie the computations.To survive,you may need...
评分这本书对于概念介绍得非常清晰,比我本科学的线代教材好太多了。本科的小朋友如果看不懂自己学校出的线代教材,强烈推荐看这本书+B站3Blue1Brown的视频~通过看视频,可以从空间角度(从本质上)理解线代中各个概念的本质 B站有一个叫“ [婆婆町] ”的博主,做了 “线性代数的本...
评分作者在开篇就给了线性代数一个很新奇的定义:“从某种意义上说,线性代数是一门语言,你要像对待外语一样,每天都学。”书中有大量的应用实例,内容结构安排的很好,前几章就引入子空间,向量,线性变换的概念,还介绍了一下线性代数的核心思想和研究内容,而后面几章的内容都...
评分昨天在图书馆翻了翻"时间序列分析"的书,发现这东西还是很有用的,利用时间作为自变量来预测一个时间序列未来的值,比如,可以预测地震、天气、股票等等,由于它的自变量只有时间,所以感觉很神奇,几乎就是拿一个变量自己来做回归,称之为自回归AR(auto regression),另...
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