This repository contains lectures and homeworks for Numerical linear algebra course. It will be updated as the class progresses.
Week | Lecture notebooks | Supplementary materials | Homework | Tests |
---|---|---|---|---|
1 | General info [GitHub, Nbviewer] Intro to Python [GitHub, Nbviewer] SVD Applications, part 1 [GitHub, Nbviewer] SVD Applications, part 2 [GitHub, Nbviewer] Matrix calculus intro [GitHub, Nbviewer] |
Data folder | Pre-term test | |
2 | Lecture 1. Floating point arithmetic, vector norms [GitHub, Nbviewer] Lecture 2. Matrix norms and unitary matrices [GitHub, Nbviewer] Lecture 3. Matvecs and matmuls, memory hierarchy, Strassen algorithm [GitHub, Nbviewer] Lecture 4. Matrix rank, low-rank approximation, SVD [GitHub, Nbviewer] |
Problem set 1 (Deadline: 15.11.2019 23:59) |
||
3 | Lecture 5. Linear systems [GitHub, Nbviewer] Lecture 6. Eigenvalues and eigenvectors [GitHub, Nbviewer] Lecture 7. Matrix decompositions and how we compute them [GitHub, Nbviewer] Lecture 8. Symmetric eigenvalue problem and SVD [GitHub, Nbviewer] |
Overview of part 1 [GitHub, Nbviewer] | Problem set 2 (Deadline: 26.11.2019 23:59) |
|
4 | Lecture 9. From dense to sparse linear algebra [GitHub, Nbviewer] Lecture 10. Sparse direct solvers [GitHub, Nbviewer] Lecture 11. Intro to iterative methods [GitHub, Nbviewer] |
Theoretical minimum questions Exam questions |
||
5 | Lecture 12. Great iterative methods [GitHub, Nbviewer] Lecture 13. Iterative methods and preconditioners [GitHub, Nbviewer] Lecture 14. Structured matrices, FFT, convolutions, Toeplitz matrices [GitHub, Nbviewer] Lecture 15. Matrix functions and matrix equations [GitHub, Nbviewer] |
Notes from lectures 12 and 13 Notes from lectures 14 and 15 |