Exploring Linear Algebra for Artificial Intelligence

You need to learn Linear Algebra in College. It's a fairly interesting topic but a little extra help would be welcome. I am Suman Mathews, math educator and teacher.

Having taught Mathematics for over three decades, I hope this course will help you in understanding Linear Algebra better. The course unravels with understanding the normal form of a matrix and how to convert a matrix to it's normal form using simple row operations.

You will also learn how to find two non singular matrices P and Q so that PAQ is the normal form. Next, you'll learn about Gaussian elimination method and Gauss Jordan method and the difference between the two. You'll learn what is an augmented matrix in this context.

As you proceed with the course, you'll learn about Gauss Siedel method and use it to solve a diagonally dominant system of equations. You'll also learn about diagonally dominant form and how to convert a set of equations to the diagonally dominant form. You'll also learn the traditional method of calculating inverse of a matrix using adjoint.

Next you'll learn about linear transformations in two or three variables and regular transformations. Learn about orthogonal transformations and how the matrix associated with an orthogonal transformation is called an orthogonal matrix. You'll dive into linear independence of vectors.

Learn about characteristic equation of a matrix and how to calculate eigenvalues and eigenvectors of a matrix using this. So enhance your knowledge with this course on Linear Algebra. Share this with your friends who may need this. Learn about Cayley Hamilton Theorem and diagonalisation of a matrix

You'll be introduced to linear transformations, orthonality of vectors and more. Learn how Vectors are used in Linear Algebra.

You'll learn about Vector Spaces and Subspaces. Also learn the necessary and sufficient conditions for subspace of a Vector Space.

Create a road map for your success.