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Open Machine Learning course

License: MIT License

Python 0.65% Jupyter Notebook 99.35%

ml-course's Introduction

Machine Learning course

First semester of girafe-ai Machine Learning course

Recordings and materials

Date	Content	Lecture video	Slides	WarmUp test	HW	Deadline	Comments
05.09.2022	Week01. Intro, Naive Bayes and kNN.	Запись лекции 2021 Запись семинара 2021	Слайды		Assignment 01: kNN	23.59 AOE, 03.10.2022	По техническим причинам запись лекции 2022 года не велась
12.09.2022	extra Week. Linear algebra recap.	Запись лекции Запись семинара 2022	Слайды
19.09.2022	Week02. Linear Regression.	Запись лекции Запись семинара 2022	Слайды		Assignment 02: Linear Regression	23.59 AOE, 10.10.2022
26.09.2022	Week03. Linear Classification.	Запись лекции Запись семинара 2022	Слайды		Lab01: ML pipeline	23.59 AOE 10.11.2022
03.10.2022	Week04. SVM, PCA.	Запись лекции Запись семинара 2022	Слайды		Assignment 03: SVM kernel	23.59 AOE, 24.10.2022
10.10.2022	Week05. Trees and ensembles	Запись лекции	Слайды		Optional assignment 04: Tree from scratch	23.59 AOE, 22.12.2022	Вместо семинара проходила контрольная работа
17.10.2022	Week06. Gradient boosting	Запись лекции Запись семинара	Слайды
24.10.2022	Week07. Разбор теста	Запись разбора					Вместо лекции были тест и разбор.
31.10.2022	Week08. Intro into Deep Learning	Запись лекции Запись семинара	Слайды
07.11.2022	Week09. Backpropogation	Запись семинара	Слайды				Лекция не велась по причине болезни преподавателя, однако был проведён дополнительный семинар по backpropogation
14.11.2022	Week10. Dropout and Batchnorm	Запись лекции Запись семинара	Слайды
21.11.2022	Week11. Embeddings and seq2seq model	Запись лекции Запись семинара	Слайды

Prerequisites

Prerequisites are located here.

Literature:

YSDA ML Book (Russian only)
Probabilistic Machine Learning: An Introduction; English link, Русский перевод
Deep Learning Book: English link. Первая часть (Part I) крайне рекомендуется к прочтению.

More additional materials are available here

Exam program:

Available here

Main authors:

Radoslav Neychev
Vladislav Goncharenko

Contributors:

Iurii Efimov
Nikolay Karpachev
Ivan Provilkov
Valery Marchenkov
Anastasia Ianina
Irina Rudenko
Fedor Ryabov

Acknowledgements:

Special thanks to:

Stanislav Fedotov, YSDA for informative discussions, program verification and support.
Konstantiv Vorontsov
Vadim Strijov for teaching this course teachers
Just Heuristic

ml-course's People

Contributors

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