Linear Algebra

Linear Algebra

Avnish

Part 24 : Diagonalization and Similarity of Matrices

Diagonalization is a process of converting a n x n square matrix into a diagonal matrix having eigenvalues of first matrix as diagonal…

Aug 23, 2019

Part 24 : Diagonalization and Similarity of Matrices

Aug 23, 2019

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Part 23 : Orthonormal Vectors, Orthogonal Matrices and Hadamard Matrix

Two vector x and y are said to be orthogonal if they are perpendicular to each other i.e. their dot product is 0.

Aug 18, 2019

Part 23 : Orthonormal Vectors, Orthogonal Matrices and Hadamard Matrix

Aug 18, 2019

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Part 22 : Eigenvalues and Eigenvectors

We multiply a vector x with A, we get another vector as a product. If that product vector points in same direction as x, then it will be…

Aug 2, 2019

Part 22 : Eigenvalues and Eigenvectors

Aug 2, 2019

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Part 21 : Properties of Determinants

We have solved determinants using Laplace expansion but by leveraging the properties of determinants, we can solve determinants much…

Jul 12, 2019

Part 21 : Properties of Determinants

Jul 12, 2019

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Part 20 : Determinants

We learned about minors and cofactors in Part 19. Now, we have per-requisite knowledge for calculating determinant of any (square) matrix.

Jun 17, 2019

Part 20 : Determinants

Jun 17, 2019

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Part 19 : Minors and Cofactors

A determinant is a scalar quantity that was introduced to solve linear equations. To compute the determinant of any matrix we have to…

Jun 7, 2019

Part 19 : Minors and Cofactors

Jun 7, 2019

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Part 18 : Norms

Norm is a function that returns length/size of vector (except zero vector).

Apr 19, 2019

Part 18 : Norms

Apr 19, 2019

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Part 17 : Projections

We have covered projections in Dot Product. Now, we will take a deep dive into projections and projection matrix.

Apr 15, 2019

Part 17 : Projections

Apr 15, 2019

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Part 16 : Dimension and Basis

The maximum number of linearly independent vectors in V will be called dimension of V. Represented as dim(V).

Mar 20, 2019

Part 16 : Dimension and Basis

Mar 20, 2019

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Part 15 : Orthogonality and four fundamental subspaces

Two vectors are said to be orthogonal if they are subtended on a right angle.

Mar 15, 2019

Part 15 : Orthogonality and four fundamental subspaces

Mar 15, 2019

Explaining the concepts of Linear Algebra and their application. View full series at: github.com/bovem/publications. Now publishing on: avni.sh
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Avnish
SQE @ Red Hat | www.avni.sh/ | linkedin.com/in/avnish-pal/

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