Linear Algebra for Data Science (2022) — различия между версиями

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| <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
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| <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]
 
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Версия 00:18, 19 сентября 2022


General information

One semester course. 6 credits.

Lecturer: Dmitri Piontkovski (Дмитрий Игоревич Пионтковский)

Class teacher: Vsevolod Chernyshev (Всеволод Леонидович Чернышев)

Telegram channel

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 Completing time 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 GitHub link
Lecture 2 16.09.22

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

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.