Linear Algebra for Data Science (2022) — различия между версиями
Материал из Wiki - Факультет компьютерных наук
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'''<span style="color:green">Topics</span>''' on which you can prepare a talk: on your own (based on your experience) or from list: ''will be published soon'' | '''<span style="color:green">Topics</span>''' on which you can prepare a talk: on your own (based on your experience) or from list: ''will be published soon'' | ||
| + | |||
| + | ===Homeworks=== | ||
| + | {| class="wikitable" | ||
| + | |- | ||
| + | ! Type!! Date !! Topics !! Download materials !! Read Materials !! Tasks !! Time to completion !! Deadline !! Download Solution !! Read Solution | ||
| + | |- | ||
| + | | <span style="color:green">Optional</span> || 14.09.22 || Pseudoinverse matrices. Skeletonization. || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/assignments/hw1.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/assignments/hw1.pdf Click] || 4 || 15-30 min || 16.09.22 || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/assignments/homeworks1_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/assignments/homeworks1_linear_algebra_for_ds.pdf Click] | ||
| + | |- | ||
| + | | Soon || soon || || || || || || | ||
| + | |} | ||
===Lectures=== | ===Lectures=== | ||
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! Lecture !! Date !! Topics !! Download materials !! Read Materials !! Pages !! Reading time !! GitHub (for changes) | ! Lecture !! Date !! Topics !! Download materials !! Read Materials !! Pages !! Reading time !! GitHub (for changes) | ||
|- | |- | ||
| − | | Lecture 1 || 09.09.22 || Distinctive features of applied linear algebra. <br> Problems with real data. Pseudoinverse matrices. Skeletonization. || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture1_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture1_linear_algebra_for_ds.pdf Click] || 3p || 7 min read || [https://github.com/addicted-by/hse_courses/tree/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture1.tex | + | | Lecture 1 || 09.09.22 || Distinctive features of applied linear algebra. <br> Problems with real data. Pseudoinverse matrices. Skeletonization. || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture1_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture1_linear_algebra_for_ds.pdf Click] || 3p || 7 min read || [https://github.com/addicted-by/hse_courses/tree/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture1.tex Click] |
|- | |- | ||
| − | | Lecture 2 || 16.09.22 || || || || || || | + | | Lecture 2 || 16.09.22 || Pseudosolutions and its applications. Linear Regression. || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture2_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture2_linear_algebra_for_ds.pdf Click] || 3p (v1.0) || 10 min read || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture2.tex Click] |
| + | |- | ||
| + | | Lecture 3 || 23.09.22 || Approximation. Interpolation problem. Polynomial interpolation.<br> Hermitian interpolation. Splines. Bézier curves and splines.|| [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture3_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture3_linear_algebra_for_ds.pdf Click] || 5(v1.5) || 10 min read || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture3.tex Click] | ||
| + | |- | ||
| + | | Lecture 4 || 07.10.22 || Metric axioms. Metric spaces. Norms. Normed linear spaces.|| [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture4_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture4_linear_algebra_for_ds.pdf Click] || 4(v1.5) || 15 min read || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture4.tex Click] | ||
| + | |- | ||
| + | | Lecture 5 || 14.10.22 || Norms. Minkovski's theorem. Euclidian space.|| [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture5_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture5_linear_algebra_for_ds.pdf Click] || 1(v0) || 12 min read || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture5.tex Click] | ||
| + | |- | ||
| + | | Lecture 6 || 21.10.22 || Chebyshev polynomials of the first kind. Chebyshev polynomials of the second kind.|| [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture6_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture6_linear_algebra_for_ds.pdf Click] || 1(v0) || 12 min read || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/lectures/lecture6.tex Click] | ||
| + | |- | ||
| + | | Lecture 7 || soon || soon || soon || soon || soon || soon || soon | ||
|} | |} | ||
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! Seminar!! Date !! Topics !! Download materials !! Read Materials !! Pages !! Reading time !! GitHub (for changes) | ! Seminar!! Date !! Topics !! Download materials !! Read Materials !! Pages !! Reading time !! GitHub (for changes) | ||
|- | |- | ||
| − | | Seminar 1 || 09.09.22 || Pseudoinverse matrices. Skeletonization. Singular value decomposition (SVD) || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/seminars/seminar1_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/seminars/seminar1_linear_algebra_for_ds.pdf Click] || | + | | Seminar 1 || 09.09.22 || Pseudoinverse matrices. Skeletonization. Singular value decomposition (SVD) || [https://github.com/addicted-by/hse_courses/raw/main/1st_year/term1/module1/linear_algebra_data_science/seminars/seminar1_linear_algebra_for_ds.pdf Click] || [https://github.com/addicted-by/hse_courses/blob/main/1st_year/term1/module1/linear_algebra_data_science/seminars/seminar1_linear_algebra_for_ds.pdf Click] || 3p || 9 min read || [https://github.com/addicted-by/hse_courses/tree/main/1st_year/term1/module1/linear_algebra_data_science/seminars/seminar1.tex GitHub link] |
|- | |- | ||
| Seminar 2 || 16.09.22 || || || || || | | Seminar 2 || 16.09.22 || || || || || | ||
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* Bryan, K. and Leise, T., 2006. The $25,000,000,000 eigenvector: The linear algebra behind Google. SIAM review, 48(3), pp.569-581; | * Bryan, K. and Leise, T., 2006. The $25,000,000,000 eigenvector: The linear algebra behind Google. SIAM review, 48(3), pp.569-581; | ||
* D. Cox, J. Little, and D. O’Shea. Ideals, varieties, and algorithms: an introduction to computational algebraic geometry and commutative algebra. Springer Science & Business Media, 2013. | * D. Cox, J. Little, and D. O’Shea. Ideals, varieties, and algorithms: an introduction to computational algebraic geometry and commutative algebra. Springer Science & Business Media, 2013. | ||
| + | |||
| + | ===Contacts=== | ||
| + | [https://t.me/gumanitariinenuzhny Polina Moskvicheva] | ||
| + | |||
| + | [https://t.me/addicted_by Aleksey Ryabykin] [https://github.com/addicted-by Github] | ||
Текущая версия на 03:25, 22 октября 2022
Содержание
General information
One semester course. 6 credits.
Lecturer: Dmitri Piontkovski (Дмитрий Игоревич Пионтковский)
Class teacher: Vsevolod Chernyshev (Всеволод Леонидович Чернышев)
Schedule
| Type | Day of week | Time | Place |
|---|---|---|---|
| Lectures | Friday | 18:10-19:30 | S224, Pokrovsky Blvd. 11 (Покровский б-р 11) |
| Seminars | Friday | 19:40-21:00 | S224, Pokrovsky Blvd. 11 (Покровский б-р 11) |
Grading system
Final Grade = 0.5 * Test1 + 0.5 * Test2 + Bonus (for a talk, ≤ 5) + Bonus (for classes, ≤1..2)
Tests: unique for everyone
Topics on which you can prepare a talk: on your own (based on your experience) or from list: will be published soon
Homeworks
| Type | Date | Topics | Download materials | Read Materials | Tasks | Time to completion | Deadline | Download Solution | Read Solution |
|---|---|---|---|---|---|---|---|---|---|
| Optional | 14.09.22 | Pseudoinverse matrices. Skeletonization. | Click | Click | 4 | 15-30 min | 16.09.22 | Click | Click |
| Soon | soon |
Lectures
All lectures you will find here
| Lecture | Date | Topics | Download materials | Read Materials | Pages | Reading time | GitHub (for changes) |
|---|---|---|---|---|---|---|---|
| Lecture 1 | 09.09.22 | Distinctive features of applied linear algebra. Problems with real data. Pseudoinverse matrices. Skeletonization. |
Click | Click | 3p | 7 min read | Click |
| Lecture 2 | 16.09.22 | Pseudosolutions and its applications. Linear Regression. | Click | Click | 3p (v1.0) | 10 min read | Click |
| Lecture 3 | 23.09.22 | Approximation. Interpolation problem. Polynomial interpolation. Hermitian interpolation. Splines. Bézier curves and splines. |
Click | Click | 5(v1.5) | 10 min read | Click |
| Lecture 4 | 07.10.22 | Metric axioms. Metric spaces. Norms. Normed linear spaces. | Click | Click | 4(v1.5) | 15 min read | Click |
| Lecture 5 | 14.10.22 | Norms. Minkovski's theorem. Euclidian space. | Click | Click | 1(v0) | 12 min read | Click |
| Lecture 6 | 21.10.22 | Chebyshev polynomials of the first kind. Chebyshev polynomials of the second kind. | Click | Click | 1(v0) | 12 min read | Click |
| Lecture 7 | soon | soon | soon | soon | soon | soon | soon |
Seminars
All seminars you will find here
| Seminar | Date | Topics | Download materials | Read Materials | Pages | Reading time | GitHub (for changes) |
|---|---|---|---|---|---|---|---|
| Seminar 1 | 09.09.22 | Pseudoinverse matrices. Skeletonization. Singular value decomposition (SVD) | Click | Click | 3p | 9 min read | GitHub link |
| Seminar 2 | 16.09.22 |
References
Main literature
- Тыртышников Е. Е. Матричный анализ и линейная алгебра. Учебное пособие. (2007)
- Беклемишев Д.В., Дополнительные главы линейной алгебры, СПБ, изд. Лань, 2008
- Шевцов Г.С. Линейная алгебра: теория и прикладные аспекты: Учеб. пособие. М.: Финансы и статистика, 2003 (или другой год издания). 576 с
- Olver, P.J., and Shakiban, C. Applied linear algebra. 2nd edition. Springer, 2018
- R. Horn and C. Jonson. Matrix analysis. 2nd edition. Cambridge Univ. Press, 2013
Additional literature
- Винберг Э.Б., Курс алгебры, М., изд. МГУ, 2002 (и последующие издания);
- Бахвалов Н., Жидков Н., Кобельков Н., Численные методы, М., изд. Бином, 2003 (или другой год издания);
- Колмогоров А.Н., Фомин С.В., Элементы теории функций и функционального анализа, М., изд. Наука, 1976 (или другой год издания);
- Aleskerov F., Ersel H., Piontkovski D. Linear Algebra for Economists. Berlin—Heidelberg, Springer, 2011;
- Bryan, K. and Leise, T., 2006. The $25,000,000,000 eigenvector: The linear algebra behind Google. SIAM review, 48(3), pp.569-581;
- D. Cox, J. Little, and D. O’Shea. Ideals, varieties, and algorithms: an introduction to computational algebraic geometry and commutative algebra. Springer Science & Business Media, 2013.
