Numerical linear algebra course, @SkolTech, Term 2, 2023

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] Lecture 1. Floating point arithmetic [Github] Lecture 2. Matrix norms. Unitary matrices. [Github]	Seminar 1 Seminar 2
2	Lecture 3 Matvecs and matmuls, memory hierarchy, Strassen algorithm [Github] Lecture 4. Matrix rank, skeleton decomposition, SVD [Github]	Seminar 4	HW1 (Deadline: November, 19, 23:59 MSK)
3	Linear systems [Github] Lecture 6. Eigenvalues and eigenvectors [Github] Lecture 7. Matrix decompositions review. How to compute QR decomposition and Schur decompositions [Github]	Seminar 6 Seminar 7
4	Symmetric eigenvalue problems [Github] Lecture 9. Randomized linear algebra [Github] Midterm
5	From dense to sparse linear algebra [Github] Lecture 11. [GitHub] Lecture 12. Intro to Iterative methods: start [Github]	Seminar 10	HW2 (Deadline: December, 6, 23:59 MSK)
6	Lecture 13. Great iterative methods [Github] Lecture 14. Iterative methods and preconditioners [Github]			Exam questions Basic questions
7	Lecture 15. FFT, convolutions [Github] Exam Exam	Seminar 11
8	Projects presentations

nla2023
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