Competencies: Mathematics > Linear Algebra
Linear Algebra
Body of Knowledge
| Topic | Description | Relevance | Career Tracks |
|---|---|---|---|
Vectors & Vector Spaces |
Vector operations, dot product, cross product, vector spaces, subspaces |
Critical |
ML Engineer, Data Scientist, Graphics Developer |
Matrix Operations |
Multiplication, transpose, inverse, rank, null space, column space |
Critical |
ML Engineer, Data Scientist, Graphics Developer |
Eigenvalues & Eigenvectors |
Eigendecomposition, diagonalization, applications to PCA and SVD |
Critical |
ML Engineer, Data Scientist |
Singular Value Decomposition |
SVD computation, dimensionality reduction, matrix approximation |
High |
ML Engineer, Data Scientist |
Linear Transformations |
Transformation matrices, rotation, scaling, projection, change of basis |
High |
ML Engineer, Graphics Developer, Data Scientist |
Orthogonality |
Orthogonal vectors/matrices, Gram-Schmidt, QR decomposition |
High |
ML Engineer, Data Scientist |
Systems of Linear Equations |
Gaussian elimination, LU decomposition, numerical stability |
High |
ML Engineer, Data Scientist, Engineer |
Tensor Operations |
Higher-dimensional arrays, tensor products, applications in deep learning |
High |
ML Engineer, AI Engineer |
Personal Status
| Topic | Level | Evidence | Active Projects | Gaps |
|---|---|---|---|---|
To be populated |
— |
— |
— |
— |