- Introduction to Linear Algebra
- Vectors
- Binary Matrix Operations
- System of Equations
- Solution Systems
- Eigen Value & Eigen Vectors
here you get to learn from vectors to equation systems to eigen value and eigenvectors . you get to analyze and learn how to work on it as well in the future as well. the perspective is the main key for upgradation in the linear algebra course for the college level all the way.
Operations on one matrix, including solving linear systems, and Gauss-Jordan elimination
Operations on two matrices, including matrix multiplication and elimination matrices
Matrices as vectors, including linear combinations and span, linear independence, and subspaces
Dot products and cross products, including the Cauchy-Schwarz and vector triangle inequalities
Matrix-vector products, including the null and column spaces, and solving Ax=b
Transformations, including linear transformations, projections, and composition of transformations
Inverses, 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) spaces of the transpose
Orthogonality and change of basis, including orthogonal complements, projections onto a subspace, least squares, and changing the basis
Orthonormal bases and Gram-Schmidt, including definition of the orthonormal basis, and converting to an orthonormal basis with the Gram-Schmidt process
Eigenvalues and Eigenvectors, including finding eigenvalues and their associate eigenvectors and eigenspaces, and eigen in three dimensions
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