Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 50 Minute(s)
Language
English
Taught by
Mahmoud Elsayed
Rating
3 views
Course Overview
Master Generative Adversarial Networks (GANs) in no time
This course is a comprehensive guide to Generative Adversarial Networks (GANs). The theories are explained in depth and in a friendly manner. After each theoretical lesson, we will dive together into a hands-on session, where we will be learning how to code different types of GANs in PyTorch, which is a very advanced and powerful deep learning framework!
The following topics will be included:
DCGANs
LSGANs
CGANs
CoGANs
SRGANs
CycleGANs
other types of GANs
Each type will include a theoretical and practical session.
Course Content
- 9 section(s)
- 20 lecture(s)
- Section 1 Introduction
- Section 2 Introduction to Generative Adversarial Networks
- Section 3 Deep Convolution Generative Adversarial Networks (DCGANs)
- Section 4 Least Square GANs
- Section 5 Conditional GANs
- Section 6 Coupled GANs
- Section 7 Super Resolution GANs
- Section 8 Cycle GANs
- Section 9 Other Types of GANs
What You’ll Learn
- Understand all the theoretical aspects in Generative Adversarial Networks (GANs)
- Master the practical skills in coding the Generative Adversarial Networks (GANs)
Skills covered in this course
Reviews
-
MMohammad Shoaib Ibne Saleem Casseem
This course was too amazing!!!
-
SSiarhei Kacahtkou
clear explanations, with a lot of code.
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CChristian Ramones
The presented code is partly inconsistent with the theoretical background presented before. The generator for example has only a devonvolutional pipeline. Another dissapointment is that there is a lot of text on the slides and sometimes the reference is missing.
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SSweta sharma
It was good but it should be improved by explaining things in depth. The theory knowledge is very less to understand the practical work.
