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Introduction In linear algebra, matrices are rectangular arrays of numbers, and operations like addition, subtraction, and multiplication follow specific rules. Below, I’ll explain each operation clearly and concisely, assuming you’re familiar with basic matrix notation. Matrix Addition Definition: Two matrices Read More …
Introduction to Principal Component Analysis In this article, you will learn about in depth about the Principal Component Analysis (PCA) technique which is used for reducing the dimension of data while preserving the variance. It is actually the transformation of Read More …
Introduction to eigen values and eigen vectors How to Find the Eigen Values and Eigen Vectors? explain with examples Eigen Values and Eigen Vectors has a great significance in many engineering problems specially in case of linear systems where we Read More …
Introduction to Matrix calculator This is an online tool that helps students for performing the arithmetic operations (addition, subtraction, and multiplication) online. It is simple and easy to use. You just need to select the order of matrices. In Matrix Read More …
Introduction to Secant Method What is the Secant method? Derivation of Secant method. The problem with the Newton Raphson’s method is that it requires the evaluation of the derivative for calculating each approximation of a root. Most of the times Read More …
Vector Space Definition in Linear Algebra what is the vector space in linear algebra? The collection of vectors (V1,V2,V3,…..) are said to form a vector space (V) if the following properties are satisfied For any two vectors u,v that belongs Read More …
Introduction to Linear system of equations How to solve system of linear equations in Linear Algebra? A linear equation in n variables x1,x2,x3,…..xn is an equation that can be written in the form of where b and coefficients are real Read More …
Introduction In mathematics, particularly in linear algebra and functional analysis, the concepts of inner product and inner product space play a crucial role in generalizing geometric ideas like length, angle, and orthogonality to more abstract settings. These concepts are foundational in fields such as Read More …
Introduction Two matrices, say A and B, are called similar if there exists an invertible matrix P such that: B=P−1AP This means that B is essentially a transformed version of A. But here’s the cool part: even though A and B might look different, they share something very special—their eigenvalues!” Eigenvalues are those Read More …
Introduction Finding extreme values of a function involves identifying the maximum and minimum values the function can achieve. These values can occur at critical points (where the derivative is zero or undefined) or at the boundaries of the domain. Steps Read More …