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 R^n 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. Students' conceptual understanding is reinforced through True/False questions, practice problems, and the use of technology. David Lay changed the face of linear algebra with the execution of this philosophy, and continues his quest to improve the way linear algebra is taught with the new Updated Second Edition. With this update, he builds on this philosophy through increased visualization in the text, vastly enhanced technology support, and an extensive instructor support package. He has added additional figures to the text to help students visualize abstract concepts at key points in the course. A new dedicated CD and Website further enhance the course materials by providing additional support to help students gain command of difficult concepts. The CD, included in the back of the book, contains a wealth of new materials, with a registration coupon allowing access to a password-protected Website. These new materials are tied directly to the text, providing a comprehensive package for teaching and learning linear algebra.
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。
评分一本非常好的线性代数基础书。 从考研以后,那些不常用到的数学知识变开始逐渐淡忘、褪色。最近对机器学习产生了兴趣,因此又重新开始温习线性代数。 这本书的内容跟中国的教材相比,并没有增加多少,甚至有些东西还有欠缺。但是跟国内图书的不同在于,它详细的讲解了每个公式...
评分这周的作业有马尔科夫链和状态转移矩阵。最后变换为求解三元和四元的微分方程组的特解。 一类解法是拉普拉斯变换之后分离s和x(t),再使用逆变换。很不幸的是我功力尚浅,变换之后得到了一个满秩的齐次线性方程组。显然求解不下去。 另一种方法是矩阵的特征值和特征向量,相应的...
评分最近想进修一下统计,遇到第一个难关就是线性代数,好多东西都忘得差不多了,只记得某年某月曾算过特征值和特征向量…… 依稀记得当年考研时候用的就是Lay老人家这本书的中文版,但想到自己已经是研究僧了,应该看看原版书了,于是决定厚颜无耻地去爱问上偷书。下...
评分因为是考研学习LA 所以看了全国被普遍采用的那本紫色的同济LA教材,看着看着我发现那本书其实只是一本 线性代数公式大全,言简意赅到一个境界了,不适合我这样的普通智商的学生参读。 后来选择了这本LA&applications 觉得很不错。每章用一个introductory example开头 让人...
不多的完整读完的几本数学书,在第一章就讲到了线性变换,附以图形和解释,也不会让人觉得太唐突,确实厉害。老外的书以书中图形多少作为书的一个亮点,国人为什么做不到呢?
评分不多的完整读完的几本数学书,在第一章就讲到了线性变换,附以图形和解释,也不会让人觉得太唐突,确实厉害。老外的书以书中图形多少作为书的一个亮点,国人为什么做不到呢?
评分大爱~~~~写的相当相当好!
评分线代基础
评分浅显易懂,适合像我这样上过线代但是需要重新捡起来的人阅读,里面给的应用也比较切合实际,Numerical Note还可以在算法上提供一些建议。比国内的教材好的不是一星半点
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