.
├── index.html
├── Lecture Notes
│ ├── 00-syllabus.html
│ ├── 01-intro.html
│ ├── 02-vectors.html
│ ├── 03-linear-independence.html
│ ├── 04-gaussian-elimination.html
│ ├── 05-gaussian-elimination2.html
│ ├── 06-vector-geometry.html
│ ├── 07-kmeans.html
│ ├── 08-cluster-evaluation.html
│ ├── 09-hierarchical.html
│ ├── 10-supervised-learning.html
│ ├── 11-decision-trees.html
│ ├── 12-knn.html
│ ├── 13-classification-comparison.html
│ ├── 14-matrix-algebra.html
│ ├── 15-real-computation.html
│ ├── 16-linear-transformations.html
│ ├── 17-matrix-composition.html
│ ├── 18-matrix-factorization.html
│ ├── 19-lu-factorization.html
│ ├── 20-lu-factorization-application.html
│ ├── 21-subspaces.html
│ ├── 22-orthogonality.html
│ ├── 23-qr-decomposition.html
│ ├── 24-least-squares.html
│ ├── 25-linear-regression.html
│ ├── 26-linear-regression.html
│ ├── 27-eigenvalues.html
│ ├── 28-diagonalization.html
│ ├── 29-symmetric.html
│ ├── 30-constrained-optimization.html
│ ├── 31-svd.html
│ ├── 32-reduced-svd.html
│ ├── 33-svd-applied.html
│ ├── 34-pca.html
│ ├── 35-markov.html
│ ├── 36-markov.html
│ ├── 37-pagerank.html
│ ├── 38-last-topics.html
│ ├── 39-final-review.html
│ ├── index.html
│ └── style.css
├── lecture-notes
└── style.css
2 directories, 45 files
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