Master Generative Adversarial Networks (GANs) in no time
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)
- Understanding the fundamentals of neural networks, convolutional neural networks, deep learning.
- Basic Programming experience (preferably in Python)
- Basic High-school Mathematics
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.
Who this course is for:
- curious about data sciences, neural networks, and deep learning
