一本很好的神书，基本上学习线性代数， 都需要从这本书开始看

Applied Linear Statistical Models By Kutner & Nachtsheim & Neter，哥伦比亚大学线性回归课程规定的教材，堪称经典，难度和深度兼具，想要了解线性回归模型朋友自取

Differential Equations and Linear Algebra (4th Edition) By 作者: C. Henry Edwards – David E. Penney – David Calvis ISBN-10 书号: 013449718X ISBN-13 书号: 9780134497181 Edition 版本: 4 出版日期: 2017-01-14 pages 页数: (768 ) Pearson纯净原版超清 $204.4 For courses in Differential Equations and Linear Algebra. Concepts, methods, and core topics covering elementary differential equations and linear algebra through real-world applications In a contemporary introduction to differential equations and linear algebra, acclaimed authors Edwards and Penney combine core topics in elementary differential equations with concepts and methods of elementary linear algebra. Renowned for its real-world applications and blend of algebraic and geometric approaches, Differential Equations and Linear Algebra introduces you to mathematical modeling of real-world phenomena and offers the best problems sets in any differential equations and linear algebra textbook. The 4th Edition includes fresh new computational and qualitative flavor evident throughout in figures, examples, problems, and applications. Additionally, an Expanded Applications website containing expanded applications and programming tools is now available. Contents Application Modules Preface 1 First-Order Differential Equations 2 Mathematical Models and Numerical Methods 3Linear Systemsand Matrices 4Vector Spaces 5Higher-Order Linear Differential Equations 6Eigenvalues and Eigenvectors 7 Linear Systems of Differential Equations 8 Matrix Exponential Methods 9 Nonlinear Systems and Phenomena 10 Laplace Transform Methods 11 Power Series Methods References for Further Study Appendix A:Existence and Uniqueness of Solutions Appendix B:Theory of Determinants Answers to Selected Problems

《Applied Numerical Linear Algebra 》和《应用数值线性代数》；中英两本；［美］James W. Demmel 著 ；

The original purpose of the book was to present a unified theoretical and conceptual framework for statistical modelling in a way that was accessible to undergraduate students and researchers in other fields. The second edition was expanded to include nominal and ordinal logistic regression, survival analysis and analysis of longitudinal and clustered data. It relied more on numerical methods, visualizing numerical optimization and graphical methods for exploratory data analysis and checking model fit. The third edition added three chapters on Bayesian analysis for general- ized linear models. To help with the practical application of generalized linear models, Stata, R and WinBUGS code were added. This fourth edition includes new sections on the common problems of model selection and non-linear associations. Non-linear associations have a long history in statistics as the first application of the least squares method was when Gauss correctly predicted the non-linear orbit of an asteroid in 1801. Statistical methods are essential for many fields of research, but a widespread lack of knowledge of their correct application is creating inaccu- rate results. Untrustworthy results undermine the scientific process of using data to make inferences and inform decisions. There are established practices for creating reproducible results which are covered in a new Postface to this edition.

泛函分析经典书目：linear and nonlinear functional analysis with applications，pdf高清版，欢迎下载

Description Object-oriented linear algebra and numerical methods library in Object Pascal - Dynamic Integef, Float, String, Boolean, Complex arrays - Input/Output routines - Linear Algebra, Numerical methods, Optimization, Signal/Data processing

斯坦福机器学习编程作业machine-learning-ex1，Linear Regression，线性回归题目，满分，2015最新作业答案

本文档是Introduction to Linear Algebra 第四版答案的课后答案，该答案方便我们研究者学习和参考

Linear Algebra and Its Applications习题解答