Глубинное обучение (курс лекций)/2020

Материал из MachineLearning.

(Различия между версиями)
Перейти к: навигация, поиск
(Lectures and seminars)
(Lectures and seminars)
Строка 46: Строка 46:
[https://github.com/nadiinchi/dl_labs/blob/master/lab_pytorch.ipynb ipynb 3]
[https://github.com/nadiinchi/dl_labs/blob/master/lab_pytorch.ipynb ipynb 3]
|-
|-
-
| 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])
+
| 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)]
+
| 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"| 6 || 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]
Строка 54: Строка 54:
| 23&nbsp;Oct.&nbsp;2020 || align="center"| 7 || Recurrent neural networks. || [https://drive.google.com/file/d/1KvSzzctOjRhYwJH_9LJJeZhMp4USTcDV/view?usp=sharing Presentation]
| 23&nbsp;Oct.&nbsp;2020 || align="center"| 7 || Recurrent neural networks. || [https://drive.google.com/file/d/1KvSzzctOjRhYwJH_9LJJeZhMp4USTcDV/view?usp=sharing Presentation]
|-
|-
 +
| 30&nbsp;Oct.&nbsp;2020 || align="center"| 8 || Recurrent neural networks memory and attention mechanisms. ||
|-
|-
-
| 20&nbsp;Nov.&nbsp;2020 || align="center"| 7 || Generative adversarial networks. || [https://yadi.sk/i/wNmNOSipwhRbWQ Part1] [https://yadi.sk/i/s5goIhh_0WxLwg Part2]
+
| 06&nbsp;Nov.&nbsp;2020 || align="center"| 9 || Reinforcement learning. Q-learning. DQN model. ||
 +
|-
 +
| rowspan="2"|13&nbsp;Nov.&nbsp;2020 || rowspan="2" align="center"| 10 || Policy gradient in reinforcement learning. REINFORCE and A2C algorithms. ||
 +
|-
 +
| Reinforcement learning implementation and multi-armed bandits. || [https://github.com/nadiinchi/dl_labs/blob/master/lab_reinforcement_en.ipynb RL notebook]<br>[https://www.youtube.com/watch?v=kopoLzvh5jY Multi-Agent Hide and Seek video]<br>[https://github.com/nadiinchi/dl_labs/blob/master/lab_bandits.ipynb Bandits notebook]<br>[https://learnforeverlearn.com/bandits/ Bayesian Bandit Explorer]
 +
|-
 +
| 20&nbsp;Nov.&nbsp;2020 || align="center"| 11 || Generative adversarial networks. || [https://yadi.sk/i/wNmNOSipwhRbWQ Part1] [https://yadi.sk/i/s5goIhh_0WxLwg Part2]
|-
|-
|}
|}

Версия 11:53, 24 ноября 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

Rules and grades

TBA

Lectures and seminars

Date No. Topic Materials
11 Sep. 2020 1 Introduction. Fully-connected networks.
Matrix calculus, automatic differentiation. Synopsis
18 Sep. 2020 2 Stochastic optimization for neural networks, drop out, batch normalization.
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
23 Oct. 2020 7 Recurrent neural networks. Presentation
30 Oct. 2020 8 Recurrent neural networks memory and attention mechanisms.
06 Nov. 2020 9 Reinforcement learning. Q-learning. DQN model.
13 Nov. 2020 10 Policy gradient in reinforcement learning. REINFORCE and A2C algorithms.
Reinforcement learning implementation and multi-armed bandits. RL notebook
Multi-Agent Hide and Seek video
Bandits notebook
Bayesian Bandit Explorer
20 Nov. 2020 11 Generative adversarial networks. Part1 Part2

Arxiv

2019

2017

2016

Личные инструменты