[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-72686":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":9,"rankLanguage":9,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":9,"pushedAt":9,"updatedAt":26,"readmeContent":27,"aiSummary":28,"trendingCount":15,"starSnapshotCount":15,"syncStatus":29,"lastSyncTime":30,"discoverSource":31},72686,"The-Art-of-Linear-Algebra","kenjihiranabe\u002FThe-Art-of-Linear-Algebra","kenjihiranabe","Graphic notes on Gilbert Strang's \"Linear Algebra for Everyone\"",null,"PostScript",21556,2565,168,1,0,6,11,48,18,45,"Creative Commons Zero v1.0 Universal",false,"main",true,[],"2026-06-12 02:03:06","English ｜ [中文(简体)](README-zh-CN.md)\n\n# The-Art-of-Linear-Algebra\n\nGraphic notes on Gilbert Strang's \"Linear Algebra for Everyone\"\n\nThe output file is \"[The-Art-of-Linear-Algebra.pdf](The-Art-of-Linear-Algebra.pdf)\"\n\nJapanese version \"[The-Art-of-Linear-Algebra-j.pdf](The-Art-of-Linear-Algebra-j.pdf)\"\n\nChinese version \"[The-Art-of-Linear-Algebra-zh-CN.pdf](The-Art-of-Linear-Algebra-zh-CN.pdf)\" and \"[kf-liu\u002FThe-Art-of-Linear-Algebra-zh-CN\u002FThe-Art-of-Linear-Algebra-zh-CN.pdf](https:\u002F\u002Fgithub.com\u002Fkf-liu\u002FThe-Art-of-Linear-Algebra-zh-CN\u002Fblob\u002Fmain\u002FThe-Art-of-Linear-Algebra-zh-CN.pdf)\" for the latest Chinese version. \n\n## Abstract\n\nI tried intuitive visualizations of important concepts introduced\nin \"Linear Algebra for Everyone\".\n\nThis is aimed at promoting understanding of vector\u002Fmatrix calculations\nand algorithms from the perspectives of matrix factorizations.\nThey include Column-Row (CR), Gaussian Elimination (LU),\nGram-Schmidt Orthogonalization (QR), Eigenvalues and Diagonalization (QΛQ'),\nand Singular Value Decomposition (UΣV').\n\n![5 Factorizations](5-Factorizations.png)\n\nAlso includes other graphics.\n\n## Map of Eigenvalues\n\n![Map of Eigenvalues](MapofEigenvalues.png)\n\n- Available in PDF \"[MapofEigenvalues](MapofEigenvalues.pdf)\"\n\n## Matrix World\n\n![Matrix World](MatrixWorld.png)\n\n- Available in PDF \"[MatrixWorld](MatrixWorld.pdf)\"\n","该项目是Gilbert Strang所著《面向大众的线性代数》一书的图形笔记。通过直观的可视化方式，它解释了包括列-行（CR）分解、高斯消元法（LU）、格拉姆-施密特正交化（QR）、特征值与对角化（QΛQ'）以及奇异值分解（UΣV'）在内的关键概念，旨在帮助读者更好地理解向量\u002F矩阵运算和算法。此外，项目还提供了特征值地图和矩阵世界等额外图形资料。适合于正在学习线性代数的学生、教育工作者或任何希望以更直观的方式掌握该领域知识的人士使用。",2,"2026-06-11 03:43:11","high_star"]