Глубинное обучение (курс лекций)/2020

(Различия между версиями)

Версия 09:51, 23 октября 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

Course chat in Telegram: link

TBA

Date	No.	Topic	Materials
11 Sep. 2020	1	Introduction. Fully-connected networks.
11 Sep. 2020	1	Matrix calculus, automatic differentiation.	Synopsis
18 Sep. 2020	2	Stochastic optimization for neural networks, drop out, batch normalization.
18 Sep. 2020	2	Convolutional neural networks, basic architectures.	Presentation
25 Sep. 2020	3	Pytorch and implementation of convolutional neural networks.	ipynb 1 ipynb 2 ipynb 3
02 Oct. 2020	4	Semantic image segmentation	Presentation (pdf) Portrait Demo (source)
09 Oct. 2020	5	Object detection	Presentation (pdf) DS Bowl 2018 (pdf)
16 Oct. 2020	6	Neural style transfer.	Presentation

@@ Строка 48: / Строка 48: @@
  | 02&nbsp;Oct.&nbsp;2020 || align="center"| 4 || Semantic image segmentation || [https://yadi.sk/d/jel16JzCmHLgBQ Presentation (pdf)]<br>[https://portrait.nizhib.ai/ Portrait Demo] ([https://github.com/nizhib/portrait-demo source])
  |-
+ | 09&nbsp;Oct.&nbsp;2020 || align="center"| 5 || Object detection || [https://yadi.sk/i/vmJJgDAAvtY6Pw Presentation (pdf)]<br>[https://yadi.sk/i/5gLFLx1R7Qfjjg DS Bowl 2018 (pdf)]
  |-
- | 16&nbsp;Oct.&nbsp;2020 || align="center"| 5 || Neural style transfer. || [https://yadi.sk/i/Hp9wbpaIEHz_pw Presentation]
+ | 16&nbsp;Oct.&nbsp;2020 || align="center"| 6 || Neural style transfer. || [https://yadi.sk/i/Hp9wbpaIEHz_pw Presentation]
  |-
  |}