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线性代数导论第五版电子版，Gilbert Strang 评分:

大名鼎鼎的Introduction to Linear Algebra ,Ed 5电子版，作者 Gilbert Strang，MIT名师，知名数学家； 真正意义上的电子版，教授很贴心的用蓝色、加粗、斜体来加强知识的组织性，对萌新很有帮助； 习题答案在 http://math.mit.edu/~gs/linearalgebra/ Gilbert Strang 的线代公开课 https://www.bilibili.com/video/av15463995 公开课课程和教材各有侧重，可以互补。
2019-07-25 上传 大小：53.00MB
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应用线性代数导论

This book is meant to provide an introduction to vectors, matrices, and least squares methods, basic topics in applied linear algebra. Our goal is to give the beginning student, with little or no prior exposure to linear algebra, a good grounding in the basic ideas, as well as an appreciation for how they are used in many applications, including data tting, machine learning and articial intelligence, tomography, navigation, image processing, nance, and automatic control systems. The background required of the reader is familiarity with basic mathematical notation. We use calculus in just a few places, but it does not play a critical role and is not a strict prerequisite. Even though the book covers many topics that are traditionally taught as part of probability and statistics, such as tting mathematical models to data, no knowledge of or background in probability and statistics is needed. The book covers less mathematics than a typical text on applied linear algebra. We use only one theoretical concept from linear algebra, linear independence, and only one computational tool, the QR factorization; our approach to most applications relies on only one method, least squares (or some extension). In this sense we aim for intellectual economy: With just a few basic mathematical ideas, concepts, and methods, we cover many applications. The mathematics we do present, however, is complete, in that we carefully justify every mathematical statement. In contrast to most introductory linear algebra texts, however, we describe many applications, including some that are typically considered advanced topics, like document classication, control, state estimation, and portfolio optimization. The book does not require any knowledge of computer programming, and can be used as a conventional textbook, by reading the chapters and working the exercises that do not involve numerical computation. This approach however misses out on one of the most compelling reasons to learn the material: You can use the ideas and methods described in this book to do practical things like build a prediction model from data, enhance images, or optimize an investment portfolio. The growing power of computers, together with the development of high level computer languages and packages that support vector and matrix computation, have made it easy to use the methods described in this book for real applications. For this reason we hope that every student of this book will complement their study with computer programming exercises and projects, including some that involve real data. This book includes some generic exercises that require computation; additional ones, and the associated data les and language-specic resources, are available on-line. If you read the whole book, work some of the exercises, and carry out computer viii Preface exercises to implement or use the ideas and methods, you will learn a lot. While there will still be much for you to learn, you will have seen many of the basic ideas behind modern data science and other application areas.

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线性代数 Gilbert Strang

Introduction to Linear Algebra 4th Edition Gilbert Strang Solution Manual for Introduction to Linear Algebra 5th Edition Gilbert Strang Linear Algebra and Its Applications 4th Edition Gilbert Strang

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线性代数导论第5版课后答案

对应mit线性代数导论（GILBERT STRANG）第5版，所有章节课后答案

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线性代数导论（第四版）

线性代数导论第四版，配合MIT的线性代数课程使用。权威的线性代数教材。

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中文翻译Introduction to Linear Algebra, 5th Edition 10.1节

多年以来我常常见到一个模型，我发现它是如此的基本和实用，于是我总是将它放在第一位。该模型由 边连在一起的点组成。这叫做图。 通常类型的图表现为函数 f(x)。这种边连节点类型的图可引出矩阵来。本章是关于图的关联矩阵 ——它表明 n 个节点是如何由 m 条边连起来的。通常 m > n，边比节点多。 对于任何 m × n 矩阵，都有 Rn 中的两个基本子空间和 Rm 中的两个基本子空间。它们是 A 与 AT 的行空间及零空间。它们的维数r,n−r及r,m−r源于线性代数最重要的定理。该定理的第二部 分是行空间与零空间的正交性。我们的目标是展示些图的实例是如何阐明这个线性代数基本定理的。 当我创建一个图及其关联矩阵时，将很容易找出其子空间维数。但我们想要子空间本身——就由 正交性来协助。将子空间与它们所在的图联系起来是必要的。通过使关联矩阵专门化，线性代数定律就 变成了基尔霍夫定律。请不要对词汇“电流”和“电压”反感。这些矩形矩阵是最合适的。

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gilbert课程线代书+课后答案，麻省理工线性代数的课程和答案

gilbert课程线代书+课后答案，麻省理工线性代数的课程和答案

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国外经典教材 线性代数 原书第七版 中文 利昂著

经典的教程，不比MIT的GILBERT STRONG写的线性代数导论差，两本都看当然更好

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线性代数第五版答案(全).pdf

线性代数第五版答案(全).pdf

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线性代数导论第五版答案--Gilbert Strang

Gilbert Strang 线性代数导论第五版答案 MIT 公开课：Gilbert Strang《线性代数》

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MIT线性代数导论笔记

MIT线性代数导论笔记

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线性代数导论（第5版）习题解答 英文文字版 非扫描版 超清晰

线性代数导论（第5版）习题解答 英文文字版 非扫描版 超清晰

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线性代数导论gilbert_strang：第四版 英文版

资源内容是gilbert_strang呕心沥血之作线性代数导论第四版，是英文版本的

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gilbert线性代数+答案

gilbert课程线代书+课后答案，麻省理工线性代数的课程书籍和答案

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线性代数 原书第七版 利昂著

其实书名应该叫线性代数及应用，经典的教程，不比MIT的GILBERT STRONG写的线性代数导论差，两本都看当然更好

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MIT经典线性代数教学视频带中文字幕百度网盘

MIT经典线性代数教学视频带中文字幕百度网盘

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麻省理工线性代数讲义中文版

麻省理工线性代数讲义中文版，就是网易公开课里面那个Gilber Strang 讲的。最好的线性代数课。当然，这个讲义网上还是很容易找到的，而且是最新最配合的，不过都是英文的。当然鼓励大家看原版的。但如果不幸，你英文不好，我这个可能是唯一的中文讲义了，分享给英文不好的童鞋。

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Lecture slides 应用线性代数导论课件PPT

Lecture slides for Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares

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