0.2.2 Linear transformations. Let U be an n-dimensional vector space and let V be an m-dimensional vector space, both over the same field F; let BU be a basis of U and let BV be a basis of V. We may use the isomorphisms x → [x]BU and y → [y]BV to rep…

搞统计的线性代数和概率论必须精通,最好要能锻炼出直觉,再学机器学习才会事半功倍. 线性代数只推荐Prof. Gilbert Strang的MIT课程,有视频,有教材,有习题,有考试,一套学下来基本就入门了. 不多,一共10次课. 链接:https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/calendar/ SES # TOPICS KEY DATES 1 The geometry of linear e…

http://groups.csail.mit.edu/graphics/classes/6.837/F03/lectures/04_transformations.ppt https://groups.csail.mit.edu/graphics/classes/6.837/F03/lectures/ Maps points (x, y) in one coordinate system to points (x', y') in another coordinate system x' =…

PS:一直以来对SVD分解似懂非懂,此文为译文,原文以细致的分析+大量的可视化图形演示了SVD的几何意义.能在有限的篇幅把这个问题讲解的如此清晰,实属不易.原文举了一个简单的图像处理问题,简单形象,真心希望路过的各路朋友能从不同的角度阐述下自己对SVD实际意义的理解,比如 个性化推荐中应用了SVD,文本以及Web挖掘的时候也经常会用到SVD. 原文:We recommend a singular value decomposition 简介 SVD实际上是数学专业内容,但它现在已经渗入到不同的领…

https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors#Graphs A               {\displaystyle A}   ,它的特征向量(eigenvector,也译固有向量或本征向量)                     v               {\displaystyle v}   经过这个线性变换[1]之后,得到的新向量仍然与原来的                     v          …

本文转载自他人: PS:一直以来对SVD分解似懂非懂,此文为译文,原文以细致的分析+大量的可视化图形演示了SVD的几何意义.能在有限的篇幅把这个问题讲解的如此清晰,实属不易.原文举了一个简单的图像处理问题,简单形象,真心希望路过的各路朋友能从不同的角度阐述下自己对SVD实际意义的理解,比如 个性化推荐中应用了SVD,文本以及Web挖掘的时候也经常会用到SVD. 原文:We recommend a singular value decomposition 简介 SVD实际上是数学专业内容,但它现在…

Deep Learning in a Nutshell: Core Concepts Share:   Posted on November 3, 2015by Tim Dettmers 7 CommentsTagged cuDNN, Deep Learning, Deep Neural Networks, Machine Learning,Neural Networks   This post is the first in a series I’ll be writing for Paral…

We Recommend a Singular Value Decomposition Introduction The topic of this article, the singular value decomposition, is one that should be a part of the standard mathematics undergraduate curriculum but all too often slips between the cracks. Beside…

A geometric interpretation of the covariance matrix Contents [hide] 1 Introduction 2 Eigendecomposition of a covariance matrix 3 Covariance matrix as a linear transformation 4 Conclusion Introduction In this article, we provide an intuitive, geometri…

看到的一篇比较好的关于SVD几何解释与简单应用的文章,其实是有中文译本的,但是翻译的太烂,还不如直接看英文原文的.课本上学的往往是知其然不知其所以然,希望这篇文能为所有初学svd的童鞋提供些直观的认识吧. A sigular value decomposition 目录(?)[-] Introduction The geometry of linear transformations The singular value decomposition How do we find the sing…