<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Linear Algebra on Sange Mehrab</title><link>https://anwarshamim01.github.io/Sang_e_Mehrab/tags/linear-algebra/</link><description>Recent content in Linear Algebra on Sange Mehrab</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 28 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://anwarshamim01.github.io/Sang_e_Mehrab/tags/linear-algebra/index.xml" rel="self" type="application/rss+xml"/><item><title>1.1 From Scalars to Vectors: Data Points, Rows, Columns, and Transpose</title><link>https://anwarshamim01.github.io/Sang_e_Mehrab/courses/course/chapter-01/section-01/</link><pubDate>Mon, 27 Apr 2026 00:00:00 +0000</pubDate><guid>https://anwarshamim01.github.io/Sang_e_Mehrab/courses/course/chapter-01/section-01/</guid><description>A careful introduction to how a single house measurement becomes a scalar, how many measurements become a vector, how rows become datasets, and how vectors are used in machine learning and neural networks.</description></item><item><title>1.2 From Matrices to Tensors: Tables, Images, Batches, and Multilinear Structure</title><link>https://anwarshamim01.github.io/Sang_e_Mehrab/courses/course/chapter-01/section-02/</link><pubDate>Tue, 28 Apr 2026 00:00:00 +0000</pubDate><guid>https://anwarshamim01.github.io/Sang_e_Mehrab/courses/course/chapter-01/section-02/</guid><description>A deep introduction to matrices and tensors for AI mathematics: data matrices, images as matrices, color images and batches as tensors, matrix operations, linear maps, rank, norms, eigenvalues, SVD, tensor order, modes, unfolding, n-mode products, tensor contractions, CP decomposition, Tucker decomposition, and the formal tensor-product view.</description></item></channel></rss>