Introduction to Generative Adversarial Networks (GANs)

Gain a better understanding of Generative Adversarial Networks (GANs), how they are created, how they train, and how they are able to create new media.

Syllabus

Introduction

GANs: Generating new worlds
What you should know

1. Origin and Examples of GANs

Introduction to GANs
Origin: Where did they come from?
How were they developed?
Early examples of GANs

2. Architecture and Training Methods

Model architecture
Training method
How the different models learn
Final model output

3. Training a Model

Create a basic GAN
Start training and compare results

4. The Future of Generative AI

Where generative AI has moved to
Where generative AI will move to

Taught by

Martin Kemka

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