<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Matrix-Operations on Ghafoor's Personal Blog</title><link>http://ghafoorsblog.com/tags/matrix-operations/</link><description>Recent content in Matrix-Operations on Ghafoor's Personal Blog</description><generator>Hugo</generator><language>en</language><managingEditor>noreply@example.com (AG Sayyed)</managingEditor><webMaster>noreply@example.com (AG Sayyed)</webMaster><copyright>Copyright © 2024-2026 AG Sayyed. All Rights Reserved.</copyright><lastBuildDate>Fri, 31 Oct 2025 11:40:28 +0000</lastBuildDate><atom:link href="http://ghafoorsblog.com/tags/matrix-operations/index.xml" rel="self" type="application/rss+xml"/><item><title>Two Dimension Numpy</title><link>http://ghafoorsblog.com/courses/ibm/fullstack-content/fullstack-pcert/07-python-datascience/04-module/006-two-dimension-numpy/</link><pubDate>Thu, 24 Jul 2025 13:30:06 +0000</pubDate><author>noreply@example.com (AG Sayyed)</author><guid>http://ghafoorsblog.com/courses/ibm/fullstack-content/fullstack-pcert/07-python-datascience/04-module/006-two-dimension-numpy/</guid><description>&lt;p class="lead text-primary"&gt;
This document covers the creation and manipulation of two-dimensional Numpy arrays, including indexing, slicing, matrix addition, scalar multiplication, Hadamard product, and matrix multiplication. Readers will learn practical techniques for working with 2D data structures in Python.
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&lt;h2 id="introduction-to-2d-numpy-arrays"&gt;Introduction to 2D Numpy Arrays&lt;/h2&gt;
&lt;p&gt;Numpy supports arrays with more than one dimension. Two-dimensional arrays are commonly used to represent matrices and tabular data. Arrays are created by casting nested lists to Numpy arrays.&lt;/p&gt;</description></item></channel></rss>