linear algebra book

Original address Mathematics is the foundation of computer technology, linear algebra is the basis of machine learning and deep learning, the best way to understand the knowledge of the data I think is to understand the concept, mathematics is not only used for exams in school, but also the essential basic knowledge of the work, in fact, there are many interesting math classes in the school There are many e

also a book, "Linear algebra should be learned", to see the watercress, it is a good reference in linear algebra. This article, to learn to think good linear algebra of the students o

Finally, I read the book Linear Algebra and Its Application David C. Lay intermittently. I have to say that it is indeed a classic book. There is a sense of mutual sorrow (in fact, I thought the book was quite good at the beginning ). I feel that the books written by foreign

Here's just a fraction of what the can do with linear algebraThe next time someone wonders what's the point of linear algebra are, send them here. I write a blog on math and programming and I see linear algebra applied to computer science all the time. Here's a short list th

more than 700, the length of the second version of the increase of nearly two-thirds, the book content richer. Finally, on the basis of the second edition, we also add the content that is not involved in the textbook of similar standard type theory, linear mapping and generalized inverse of matrices based on elementary factors in general number field.Different from the general higher

Linear algebra is the basis of machine learning, as early as six months ago we have developed linear algebra learning, of course, for machine learning, linear algebra is not to achieve the degree of mastery can be, more of the con

This article is a basic learning blog from the University of Paris, PhD Hadrien Jean, which aims to help beginners/Advanced Beginners Master the concept of linear algebra based on deep learning and machine learning. Mastering these skills can improve your ability to understand and apply a variety of data science algorithms.For beginners, the theoretical underpinnings of deep learning (Ian Goodfellow, Yoshua

the linear Equation Group general solution, This allows us to directly transform the vector equation into an augmented matrix to solve the problem.Meaning of the span symbol: based on a linear combination of concepts, we remember that span (V1,v2,v3,..., vn) represents a collection of all linear combinations of v1~vn of these n vectors.Based on this concept of t

of "description".For a linear transformation, as long as you select a set of bases, you can find a matrix to describe the linear transformation. To change a group of bases, you get a different matrix. All of these matrices are a description of the same linear transformation, but they are not linear transformations the

Directory Linear Algebra I. Basic Knowledge Ii. vector operations Iii. Matrix Operations Linear Algebra 1. Basic Knowledge All vectors in this book are in the form of column vectors:\ [\ Mathbf {\ VEC x} = (x_1, x_2, \ cdots, X_n) ^ t = \ begin {bmatrix} X

The core of Linear Algebra: Vector Model Is linear algebra an objective natural law or a human design? The commonality of all programming languages is that a set of models are established, a set of syntaxes are defined, and each syntax is mapped to specific semantics. Compliance between programmers and language impleme

may go through these stages again and again. You can only have a superficial impression when you first read a chapter, but after you have done exercises and built intuition, you can come back and read them again to have a deeper understanding, that is, to learn from the new. Study, even if you are not a student This process is not only applicable to students, but also helps to learn complex skills or accumulate professional knowledge on a topic. Learning skills like programming or design, mos

may go through these stages again and again. You can only have a superficial impression when you first read a chapter, but after you have done exercises and built intuition, you can come back and read them again to have a deeper understanding, that is, to learn from the new. Study, even if you are not a student This process is not only applicable to students, but also helps to learn complex skills or accumulate professional knowledge on a topic. Learning skills like programming or design, mos

For professional software such as engineering and graphics, a large amount of mathematical computation is required, and linear algebra is the most used. So, on top of. net, especially on. NET 4.0 and vs2010, how can we complete Related Linear Algebra computing? I want to use the following methods: I. self-built and

Make a mark and have time to summarize the knowledge of the linear algebra obtained in the 10-day course to finish a book.1. Determinant: The value can be evaluated2, Matrix: There is a corresponding determinant, the matrix itself can not calculate a value, but can be by the equivalent determinant of the value of the matrix and the adjoint matrix, whether reversi

Link:http://www.cnblogs.com/redmoon/archive/2011/03/29/1999242.htmlFor the engineering class, graphics and other professional software, need a lot of mathematical calculations, and the most used is the calculation of linear algebra.So, on top of. NET, and above all, how do you complete the related linear algebra calculations above. NET 4.0 and VS2010? I think the

simplification 5.2 learn faster strategies 5.3 study, even if you are not a student 1 Article: Challenge mit Computer Courses Recently, my friend Scott Young made an amazing feat: within a year, he completed all 33 of the legendary mit computer science curriculum, from Linear Algebra to Computational Theory. The most important thing is that he is self-taught. He watches online tutorial lectures and uses ac

of the lectures Started by this teacher are very good, because our linear algebra textbooks are similar. They all start from the determinant, followed by the matrix followed by the vector, I didn't quite understand the arrangement of books before, but now I am wearing it all at once: Linear Algebra is used as a too

This paper is Gilbert Strang's introductory course note on linear algebra. Course Address: http://v.163.com/special/opencourse/daishu.html 24th class: Markov Matrix, Fourier seriesThis lecture explains the application of eigenvalue, Markov matrix theory, Fourier series (it is the ingenious application of projection matrix) Markov matricesSatisfies two properties: 1) All elements are greater than or equal

inner product can also be applied naturally to any dimension of space.With the concept of distance, of course we have to do something interesting with it. or from the concept of geometry, we can use distance to calculate the perimeter and area of a plane graph and the volume of the spatial graph. For example, we can calculate the coordinates of a point in a line or a plane that is closest to the nearest point on the straight or flat plane. The two applications in mathematics, the former produce