Linear Algebra
Vectors, matrices, elimination, vector spaces, orthogonality, determinants, eigenvalues, SVD — the language of portfolios and factor models.
Topics
Following MIT OpenCourseWare 18.06 (32 lectures), grouped into 15 topics. New topics go live one at a time.
- 01Vectors & linear equationsLive
- 02Elimination, A = LU & permutationsComing soon
- 03Inverses & transposesComing soon
- 04Vector spaces, column space & nullspaceComing soon
- 05Independence, rank & the four subspacesComing soon
- 06Graphs & networksComing soon
- 07Orthogonality & projectionsComing soon
- 08Least squares & Gram–SchmidtComing soon
- 09Determinants & Cramer's ruleComing soon
- 10Eigenvalues, diagonalization & powersComing soon
- 11ODEs, Markov chains & FourierComing soon
- 12Positive definite matrices & minimaComing soon
- 13Complex matrices, FFT & Jordan formComing soon
- 14SVD & linear transformationsComing soon
- 15Change of basis & pseudoinverseComing soon