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Alexandr Katrutsa authored Nov 8, 2020
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Expand Up @@ -6,3 +6,4 @@ This repository contains lectures and homeworks for Numerical linear algebra cou
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|1| General info [[GitHub](lectures/general_info.ipynb)] <br> Lecture 1. Floating point arithmetic, vector norms [[GitHub](./lectures/lecture1/lecture-1.ipynb)] <br> Lecture 2. Matrix norms and unitary matrices [[GitHub](./lectures/lecture2/lecture-2.ipynb)] <br> Lecture 3. Matvecs and matmuls, memory hierarchy, Strassen algorithm [[GitHub](./lectures/lecture3/lecture-3.ipynb)] | [Brief Python intro](./after_lectures/3/brief_python_intro.ipynb) <br> [JAX intro](./after_lectures/3/jax_autodiff_tutorial.ipynb) | [Home assignment 1](https://github.com/oseledets/nla2020/blob/main/hw/hw1/hw1.ipynb) <br> Deadline: November, 8, 23:59 MSK |
| 2 | Lecture 4. Matrix rank, low-rank approximation, SVD [[GitHub](./lectures/lecture4/lecture-4.ipynb)] <br> Lecture 5. Linear systems [[Github](./lectures/lecture5/lecture-5.ipynb)] <br> Lecture 6. Eigenvalues and eigenvectors [[GitHub](./lectures/lecture6/lecture-6.ipynb)] | [PyTorch intro](./after_lectures/4/pytorch_intro.ipynb) | |
| 3 | Lecture 7. Matrix decompositions and how we compute them [[GitHub](./lectures/lecture7/lecture-7.ipynb)] | | | |

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