Linear Algebra Practice
Cover matrix fundamentals, subspaces, projections, spectral structure, and decomposition.
Recommended resources
- MIT 18.06 Linear Algebra — MIT OpenCourseWare
Instructions
- Split the set across sessions.
- Retry every hinted item independently.
Ordered items
- Matrix fundamentals under time pressure
- Basis, dimension, and coordinates
- Nullspace, column space, pivots, and block structure
- Projection matrix as geometry and spectrum
- Least squares, QR, and orthonormal projection
- Symmetry, orthogonality, and eigenspaces
- Positive definite and semidefinite transformations
- Singular value decomposition from the Gram matrix
- Low-rank error and explained variance
Completion
Explain the algebraic and geometric meaning of rank, projection, eigenstructure, and SVD.