Panda-metrics-2024-25 — различия между версиями
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) |
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| Строка 31: | Строка 31: | ||
2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression. | 2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression. | ||
| + | 2024-09-09, lecture 2: Geometry of regression. Fitted vector is the projection of y-vector onto the Span of regressors. Hat-matrix: definition, simple properties. | ||
| + | SST, SSE, SSR: definition, Pythagorean theorem: SST = SSE + SSR. | ||
== Sources of Wisdom == | == Sources of Wisdom == | ||
Версия 22:50, 9 сентября 2024
Содержание
What-about
Course goals
侍には目標がなく道しかない [Samurai niwa mokuhyō ga naku michi shikanai]
A samurai has no goal, only a path.
Telegram channel, Telegram chat
Lectures video recordings
Grading
Semester-1 grade = 0.2 HA-1 + 0.4 Exam-Alpha + 0.4 Exam-Beta.
Semester-2 grade = 0.2 HA-2 + 0.4 Exam-Gamma + 0.4 Exam-Delta.
Final course grade = 0.5 Semester-1 grade + 0.5 Semester-2 grade
Home assignments
Home assignments have equal weights. You have 4 honey weeks for the entire course.
Exams
Samurai diary
2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression.
2024-09-09, lecture 2: Geometry of regression. Fitted vector is the projection of y-vector onto the Span of regressors. Hat-matrix: definition, simple properties. SST, SSE, SSR: definition, Pythagorean theorem: SST = SSE + SSR.
Sources of Wisdom
CausML: Causality in ML book with python and R code
MPro-en: Problem set for classes (translation in progress)
MPro-ru: Problem set for classes (in Russian)
