Warning: The following USES generic linear algebra libraries; use it only as a guideline.
警告：下面使用了普通的线性代数库；使用它只是作为一个参考。
So the nice thing about arrays is, you can use them to do the kinds of things you, if you ever took a linear algebra course, you learned about doing.
所以行列式的优点就是，你可以让它们做一些事情，如果你是在上线性代数课的话，你就会学到这些。
They should teach Linear Algebra immediately after algebra. It's pretty easy, and it's amazingly useful in all sorts of domains, including machine learning.
代数和线性代数(比如,矩阵).他们会在教完代数后立即教线性代数.这也简单,这但相当多的领域非常有用,包括机器学习.
Its main advantage over traditional mathematical notation for linear algebra is that it's much easier to type.
同线性代数传统的数学标记法相比，其主要优点是更易于输入。
Even though two-dimensional arrays are similar to matrices from linear algebra, operations (such as multiply) have nothing to do with the operations in linear algebra (such as matrix multiplication).
虽然二维数组与线性代数中的矩阵类似，但是对它们的操作(比如乘)与线性代数中的操作(比如矩阵乘)是完全不同的。
It's a general fact that you will see more in detail in linear algebra if you take it.
如果你学线性代数的话,就会学到更多细节。
Finally, JAMA is not a general-purpose array class. Instead, it focuses on the principle mathematical functionality required to do numerical linear algebra.
最后，jama也不是一个通用的数组类，相反，它主要关注于与矩阵数值计算相关的数学运算。
You may want to note that this is the first volume, and that the second volume is also worth getting: Calculus, vol. 2: Multi-Variable Calculus and Linear Algebra with Applications.
你会发现这是他它的第一卷，并且第二卷也值得去读：微积分卷2：多远微分与与线性代数及其应用。
The text for the course is this book, Introduction to Linear Algebra.
该课程的教材是这本书：线代入门。
一些线性代数。
Fine, this is the first lecture in MIT's course 18.06: Linear Algebra.
很好，这是MIT课程18.06的第一讲：线性代数。
You do need to have very good linear algebra skills.
你需要有很好的线性代数技能。
A basic knowledge of factor analysis is required and a working knowledge of linear algebra is helpful.
因子分析的基本知识是必要的，对线性代数的工作经验是有益的。
Algebra and Linear algebra (i. e. matrices). They should teach Linear algebra immediately after algebra. It's pretty easy and it's amazingly useful in all sorts of domains including machine learning.
代数和线性代数(比如：矩阵)，他们会在教完代数后立即教线性代数。这也简单，但这在相当多的领域非常有用，包括机器学习。
Matrix proofs of several theorems in linear algebra are given.
摘要给出了线性代数中几个定理的矩阵证法。
, this is my plan, the fundamental problem of linear algebra, which is to solve a system of linear equations.
，这是我的计划：线代的基本问题是用来解线性方程组（systemof linear equations）。
The mathematical content of this course involves some linear algebra, probability theory, algebra, combinatorics and topics from a variety of other fields.
这门课程用的数学涉及到线性代数、机率论、代数、组合学和各式其他的相关领域。
If something comes up again and again (like algebra and linear algebra), then I'll start doing some exercises to make sure I really understand it.
如果某些问题(比如代数和线性代数)一次又一次的出现，我就做些练习去确认我是否真正的理解它了。
更多的线性代数。
Familiarity with multivariable calculus, linear algebra, and probability and statistics is required.
熟悉多变量微积分，线性代数，概率和统计是必需的。
College: Differential and Integral Calculus, Differential Equations, Linear Algebra, Probability and Statistics, Discrete Math.
大学：微积分，微分公式，线性代数，概率和统计，离散数学。
The matrix factorization and its modification is one of the most effective techniques in numerical linear algebra.
矩阵分解的校正技术是数值线性代数中最有效的工具之一。
Blind image restoration has a strong background of mathematics, including estimation theory, ill-posed problem solution method, linear algebra, stochastic process, numerical analysis, and so on.
图像盲复原具有很强的数学背景，同估计理论、病态逆问题求解理论、线性代数、随机过程和数值分析等都有着密切的联系。
Linear relation of vector group is an important concept in linear algebra and is also an important theoretical foundation of solving problems.
向量组的线性相关性是线性代数中的重要概念，也是解决问题的重要的理论根据。
This paper discussed the matrix of elementary transformation in the higher elementary algebra linear algebra and number theory in wide use.
本论文主要讨论了矩阵的初等变换在高等代数线性代数以及初等数论中的广泛运用。
This paper describes the relationship between the rank of matrix, the rank of vector group and liner equation group in the linear algebra.
讨论了线性代数中矩阵的秩、向量组的秩与线性方程组的秩之间的关系。
Recursion is a new effective method for computing dense linear algebra.
递归算法是计算稠密线性代数的一种新的有效方法。
Recursion is a new effective method for computing dense linear algebra.
递归算法是计算稠密线性代数的一种新的有效方法。
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