by Amit Shekhar · 4 June 2026
Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs), one of the most fascinating ideas in Machine Learning that can create brand new images, faces, and art that never existed before.
Read on Outcome School ↗then come back to lock it in
Before you read, guessHow many neural networks are contained within a GAN?
Ten seconds, a guess, then read — a wrong guess still makes the answer stick.
What this article covers
- What is a Generative Adversarial Network (GAN)?
- The two players: Generator vs Discriminator
- The counterfeiter vs police analogy
- The adversarial training loop
- The loss function and the minimax game in simple words
- A tiny PyTorch-style code sketch
- The mode collapse problem
- Training stability
- Types of GANs (DCGAN, Conditional GAN, StyleGAN, CycleGAN)
- Real-world applications of GANs
The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.