Linear Algebra:
Vectors, vector spaces, linear transformations, multilinear map, inner product spaces, norms, orthogonality, Gram-Schmidt algorithm, QR-factorisation, least square, Householder algorithm, normal matrices, Jordan canonical forms, Cayley-Hamilton theorem, minimal and characteristic polynomials, direct sum decompositions, generalised eigenspaces, functions of matrices, exponentials of matrices, etc will be studied in this course. Such material can be applied to linear programming, computer graphics, fractals, and many areas in natural sciences and social sciences.

• Beezer R. A First Course in Linear Algebra (FREE!)
• Bowen R.M. and Wang C-C. Introduction to Vectors and Tensors (FREE!)
• Chen W.W.L. Linear Algebra (FREE!) - Read Chapter n's, for integer n>7.
• Dawkins P. Linear Algebra (FREE!)
• Fraleigh J.B. and Beauregard R.A. Linear Algebra - Not excellent for a first course.
• Halmos P.R. Finite-Dimensional Vector Spaces 
• Halmos P.R. Linear Algebra Problem Book 
• Hefferon J. Linear Algebra (FREE!)
• Herod J.V. Linear Algebra, Infinite Dimensions, and Maple (FREE!)
• Ikenaga B. Notes on Linear Algebra (FREE!)
• Kuttler K. An Introduction To Linear Algebra [.pdf] (FREE!)
• Lang S. Linear Algebra - As Lang had said this book isn't aimed for introductory linear algebra, it goes beyond standard first course of linear algebra. Make sure you have a solid foundation before you read this.
• Meyer C.D. Matrix Analysis and Applied Linear Algebra (FREE!)
• Sharipov R. Course of Linear Algebra and Multidimensional Geometry (FREE!)
• Shilov G.E. Linear Algebra - Professor Shilov at the Moscow State University states that this text "considers spaces over an arbitrary field, with the real and complex spaces being considered as closely related special cases of the general theory."

国外统计书目+免费教材/讲义

https://bbs.pinggu.org/thread-311802-1-1.html