Become a Linear Algebra Master includes operations on one matrix, including solving linear systems, and Gauss-Jordan elimination . Matrices as vectors, including linear combinations and span, linear independence, and subspaces . Transformations, including invertible and singular matrices, and solving systems with inverse matrices . Determinants, including upper and lower triangular matrices and Cramer’s rule . Transposes, including their determinants, and the null (left null) and column (row) The Cauchy-Schwarz and vector triangle inequalities of matrices are discussed in the book, “Becoming a linear algebra master”Authentication failed. Unique API key is not valid for this user.
Who this course is for:
Current Linear Algebra students, or students about to start Linear Algebra who are looking to get ahead
Anyone who wants to study math for fun after being away from school for a while
Anyone who needs Linear Algebra as a prerequisite for Machine Learning, Deep Learning, Artificial Intelligence, Computer Programming, Computer Graphics and Animation, Data Analysis, etc.
