Глубинное обучение (курс лекций)/2020
Материал из MachineLearning.
(Различия между версиями)
(Новая: __NOTOC__ This is an introductory course on deep learning models and their application for solving different applied problems of image and text analysis. '''Instructors''': [[Участ...) |
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!Date !! No. !! Topic !! Materials | !Date !! No. !! Topic !! Materials | ||
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| - | | | + | | rowspan="2"|11 Sep. 2020 || rowspan="2"|1 || Introduction. Fully-connected networks. || |
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| - | + | | Matrix calculus, automatic differentiation. || [https://drive.google.com/file/d/1Yu790uIPyxp9JIyysxfJDor_LJQu83gQ/view?usp=sharing Synopsis] | |
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Версия 19:21, 15 сентября 2020
This is an introductory course on deep learning models and their application for solving different applied problems of image and text analysis.
Instructors: Dmitry Kropotov, Victor Kitov, Nadezhda Chirkova, Oleg Ivanov and Evgeny Nizhibitsky.
The timetable in Autumn 2020: Fridays, lectures begin at 10-30, seminars begin at 12-15, zoom-link
Lectures and seminars video recordings: link
Anytask invite code: ldQ0L2R
For questions: [course chat in Telegram]
Rules and grades
TBA
Lectures and seminars
| Date | No. | Topic | Materials |
|---|---|---|---|
| 11 Sep. 2020 | 1 | Introduction. Fully-connected networks. | |
| Matrix calculus, automatic differentiation. | Synopsis |
