Basic Math and Pre-Algebra For Dummies(2nd) 英文无水印原版pdf 第2版 pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

Gilbert Strang编写的Introduction to Linear Algebra第五版习题解答 清晰

线性代数及其应用Linear Algebra and Its Applications, 4th-Gilbert Strang， 中文+英文 高清+书签

Gilbert Strang的线性代数。经典巨作

线性代数领域的经典图书，MIT教授多年教学成果，国外专用考试指定用书，亦是模式识别，机器学习必备经典图书

线性代数的讲义，供大家下载学习，这个当时找了好久，

MIT 大牛Gilbert Strang 编写的《 Introduction to Linear Algebra》第五版 2016年出版的，是网易公开课http://open.163.com/special/opencourse/daishu.html：MIT公开课：线性代数的指定教程，视频中所讲的新的内容在第四版中没有，在这个版本中有对应的章节。配套此教材同时观看Gilbert Strang大牛的公开课，深入掌握线性代数不再是难事！

The solution manual for linear algebra

TOPICS Chapters 1-6 provide coverage of applied linear algebra sufficient for reading the remainder of the book. Chapter 1: Matrices The chapter introduces matrix arithmetic and the very important topic of linear transformations. Rotation matrices provide an interesting and useful example of linear transformations. After discussing matrix powers, the concept of the matrix inverse and transpose concludes the chapter. Chapter 2: Linear Equations This chapter introduces Gaussian elimination for the solution of linear systems Ax = b and for the computation of the matrix inverse. The chapter also introduces the relationship between the matrix inverse and the solution to a linear homogeneous equation. Two applications involving a truss and an electrical circuit conclude the chapter. Chapter 3: Subspaces This chapter is, by its very nature, somewhat abstract. It introduces the concepts of subspaces, linear independence, basis, matrix rank, range, and null space. Although the chapter may challenge some readers, the concepts are essential for understanding many topics in the book, and it should be covered thoroughly. Chapter 4: Determinants Although the determinant is rarely computed in practice, it is often used in proofs of important results. The chapter introduces the determinant and its computation using expansion byminors and by rowelimination. The chapter ends with an interesting application of the determinant to text encryption. Chapter 5: Eigenvalues and Eigenvectors This is a very important chapter, and its results are used throughout the book. After defining the eigenvalue and an associated eigenvector, the chapter develops some of their most important properties, including their use in matrix diagonalization. The chapter concludes with an application to the solution of systems of ordinary differential equations and the problem of ranking items using eigenvectors. Chapter 6: Orthogonal Vectors and Matrices This chapter introduces the inner product and its associati

MIT的线性代数公开课，Gilbert Strong 老爷子的课程资料。包含讲稿，习题等等资料。个人觉得讲的很好，对于矩阵分析基础不好的同学可以多看多学一点