Linear Algebra: Canonical BasisExplores the canonical basis in linear algebra, focusing on matrix representation, diagonalizability, and characteristic polynomials.
Building Ramanujan GraphsExplores the construction of Ramanujan graphs using polynomials and addresses challenges with the probabilistic method.
Diagonalization of MatricesExplores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.
Linear Algebra: DiagonalizationExplores the diagonalization of matrices and the conditions for exact diagonalization, with examples demonstrating the process.
Clustering: K-means & LDACovers clustering using K-means and LDA, PCA, K-means properties, Fisher LDA, and spectral clustering.
Eigenvalues and Eigenvectors in 3DExplores eigenvalues and eigenvectors in 3D linear algebra, covering characteristic polynomials, stability under transformations, and real roots.
