Master GANs from Scratch: Implement 11 Game-Changing Models

From Theory to Application: The Ultimate Beginner’s Guide to Mastering GANs Hands-On with PyTorch


What you'll learn
How Generative Adversarial Networks (GANs) work
Implementation of GANs from scratch using PyTorch
Deep analysis of GANs: opening the black box
Review of impactful research papers

Requirements
Basic programming knowledge
Basic Machine Learning knowledge

Description
While
diffusion models
are the current hype,
Generative Adversarial Networks (GANs)
remain
state-of-the-art
due to their
speed
and efficiency. Despite the buzz around diffusion, GANs are still widely used in industry, and research shows that with the same compute and data, GANs can produce samples as good as diffusion models (
GigaGAN paper
). This course will equip you with everything you need to master GANs, implement them from scratch using PyTorch, and stay competitive in the field of
Generative AI
.
In this course, we will dive deep into 11 influential research papers that shaped the development of GANs. By building each model step by step, you’ll gain hands-on experience in creating powerful GAN architectures, from the original GAN to advanced models.
Why Choose This GAN Course?
Hands-on PyTorch Implementation
: Build GANs from the ground up with practical PyTorch tutorials.
Review 11 Key Papers
: Understand and implement seminal GAN models, from the original architecture to cutting-edge variants.
Master GAN Loss Variants
: Implement and train models using vanilla
GAN
,
LSGAN
,
WGAN
,
WGAN-GP
, and
Feature Matching
loss functions to solve real-world challenges.
What You'll Achieve:
Implement GANs from scratch using PyTorch
Train and evaluate models like
ALI
,
LSGAN
,
WGAN
,
WGAN-GP
,
Pix2Pix
, and
CycleGAN
to tackle real-world challenges.
Master adversarial training techniques
Apply GANs to solve real-world AI challenges
Enroll Today and Start Building GANs from Scratch!
Stay ahead of the curve in
Generative AI
by mastering GANs—
faster
, and just as powerful as diffusion models when properly trained.
Join us now
and get hands-on with cutting-edge GAN research and implementation!
Who this course is for:
To engineers and programmers
To students and researchers
To entrepreneurs, CEOs and CTOs
Machine Learning enthusiast

More Info