We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.

✖
  • A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedFor visually-impairedUser profile (HSE staff only)SearchMenu
HSE University
User profile (HSE staff only)Search
Advanced search

Course Syllabus

Course Syllabus


 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Postgraduate course 2022/2023

Generative Models in Machine Learning

Type: Elective course
Area of studies: Computer and Information Scienc
Delivered by: School of Data Analysis and Artificial Intelligence
Where: Faculty of Computer Science
When: 2 year, 1 semester
Mode of studies: offline
Open to: students of one campus
Instructors: Attila Kertesz-Farkas
Language: English
ECTS credits: 8
Contact hours: 36

Course Syllabus

Ask Question

Abstract

This course gives an introduction to generative models which aim at learning a probabilistic representation of the data (distribution). After completing the study of the discipline the PhD student should have knowledge about probabilistic models, knowledge about modern methods such as deep learning techniques, knowledge about ongoing developments in Machine Learning, hands-on experience with large scale machine learning problems, knowledge about how to design and develop machine learning programs using a programming language such as R or Python, and be able to think critically with real data.