VECTOR_SPACES
Matrices & Operations
Handling multi-dimensional data grids. Multiplications, determinants, and inverses are the engine of 3D graphics and ML algorithms.
[ a b ] * [ x ] = [ ax + by ]
[ c d ] [ y ] [ cx + dy ]Eigen_Everything
Eigenvalues and Eigenvectors represent the "axis" of transformation. Crucial for Principal Component Analysis (PCA) and dimensionality reduction.
Av = λvTRANSFORMATIONS
SCALE_ROTATE
Linear mapping: T(u + v) = T(u) + T(v)
Essential for modern AI and Neural Network architectures.
UTILITY_TOOLKIT
NumPy Operations
Industry standard for matrix math.
SVD Analysis
Singular Value Decomposition.
Dot Product Logic
Similarity measurement in vectors.
Cross Product
Normal vectors in 3D geometry.