<?xml version="1.0"?>
<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="ru">
	<id>https://www.wikicshse.ru/index.php?action=history&amp;feed=atom&amp;title=Mlds_deep_leaning_2021_2022</id>
	<title>Mlds deep leaning 2021 2022 - История изменений</title>
	<link rel="self" type="application/atom+xml" href="https://www.wikicshse.ru/index.php?action=history&amp;feed=atom&amp;title=Mlds_deep_leaning_2021_2022"/>
	<link rel="alternate" type="text/html" href="https://www.wikicshse.ru/index.php?title=Mlds_deep_leaning_2021_2022&amp;action=history"/>
	<updated>2026-06-08T04:01:51Z</updated>
	<subtitle>История изменений этой страницы в вики</subtitle>
	<generator>MediaWiki 1.45.3</generator>
	<entry>
		<id>https://www.wikicshse.ru/index.php?title=Mlds_deep_leaning_2021_2022&amp;diff=486&amp;oldid=prev</id>
		<title>imported&gt;SavelyProkhorov: add playlist link</title>
		<link rel="alternate" type="text/html" href="https://www.wikicshse.ru/index.php?title=Mlds_deep_leaning_2021_2022&amp;diff=486&amp;oldid=prev"/>
		<updated>2022-04-16T18:53:54Z</updated>

		<summary type="html">&lt;p&gt;add playlist link&lt;/p&gt;
&lt;p&gt;&lt;b&gt;Новая страница&lt;/b&gt;&lt;/p&gt;&lt;div&gt;[https://github.com/pet67/hse_mlds_deep_learning_course/edit/main/README.md github]&lt;br /&gt;
[https://www.youtube.com/playlist?list=PLDa1nku7NnMlRfI3jvKJ7mzYPXrHafQY5 videos]&lt;br /&gt;
&lt;br /&gt;
==Description==&lt;br /&gt;
Deep learning course for HSE Master’s Programme &amp;quot;Machine Learning and Data-Intensive Systems&amp;quot;&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
This course is strongly based on materials from other great HSE DL courses:&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
1.https://github.com/hse-ds/iad-deep-learning&lt;br /&gt;
&amp;lt;br&amp;gt;&lt;br /&gt;
2.https://github.com/yandexdataschool/Practical_DL&lt;br /&gt;
&lt;br /&gt;
All used materials from other cources has corresponding references.&lt;br /&gt;
&lt;br /&gt;
[https://docs.google.com/spreadsheets/d/1HsnOGvWdisYb4MHoCPfKvdNIit2IohSrhOayFPP_Q00/edit?usp=sharing grades]&lt;br /&gt;
Your Grade = round(0.3 * hw_1  + 0.3 * hw_2 + 0.3 * hw_3 + 0.1 * exam)&lt;br /&gt;
&lt;br /&gt;
Also, some weeks contain additional homeworks with extra points&lt;br /&gt;
&lt;br /&gt;
Link to course playlist on YouTube: https://www.youtube.com/playlist?list=PLmA-1xX7IuzBVeu30nVOscRJ4Xqazk-BY&lt;br /&gt;
&lt;br /&gt;
==Deadlines==&lt;br /&gt;
The deadline for completing homework will be announced along with the homework.&lt;br /&gt;
&lt;br /&gt;
Deadline for every extra homework **is next seminar**.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
==Syllabus==&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
 ! Неделя !! Тема &lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;1&amp;#039;&amp;#039;&amp;#039; || Introduction to DL and backpropagation&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;2&amp;#039;&amp;#039;&amp;#039; || DL libraries&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;3&amp;#039;&amp;#039;&amp;#039; || Convolutional neural networks&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;4&amp;#039;&amp;#039;&amp;#039; || Modern architectures of convolutional neural networks&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;5&amp;#039;&amp;#039;&amp;#039; || Metric learning&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;6&amp;#039;&amp;#039;&amp;#039; || Autoencoders and generative models&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;7&amp;#039;&amp;#039;&amp;#039; || Introduction to text processing&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;8&amp;#039;&amp;#039;&amp;#039; || Recurrent neural networks, seq2seq tasks&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;9&amp;#039;&amp;#039;&amp;#039; || Attention mechanisms and transformers&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;10&amp;#039;&amp;#039;&amp;#039; || Basics of sound processing&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;11&amp;#039;&amp;#039;&amp;#039; || Recommendation systems&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;12&amp;#039;&amp;#039;&amp;#039; || Graph models&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;13&amp;#039;&amp;#039;&amp;#039; || Reinforcement Learning&lt;br /&gt;
|-&lt;br /&gt;
| style=&amp;quot;background:#eaecf0;&amp;quot; | &amp;#039;&amp;#039;&amp;#039;14&amp;#039;&amp;#039;&amp;#039; || Additional deep Learning topics&lt;br /&gt;
|-&lt;br /&gt;
|}&lt;/div&gt;</summary>
		<author><name>imported&gt;SavelyProkhorov</name></author>
	</entry>
</feed>