Introduction to Generative Adversarial Networks (GANs) (2023)
29mBeginner2023-03-30
Authors

Martin Kemka
Martin Kemka is the founder of Northraine, a machine learning production house.
Course details
Recently, you’ve probably seen the impacts of large-scale generative art, generative text, and generative movies. Do you want to understand the basics of how this type of AI works? In this course, Martin Kemka, founder of the machine learning production house Northraine, introduces you to a very important component in the world of generative AI: Generative Adversarial Networks (GANs). Learn about the history of GANs, including where they came from and how they changed over the last decade. Find out how to train a model as you examine the model architecture and how the structure of multiple models works together. Get hands-on experience training a simple model in Jupyter Notebook. Plus, get insights on the current state of GAI and thoughts on where it’s going next.
Skills covered
Generative AIFoundationsArtificial Intelligence (AI)
Concepts
0. Introduction
- 01 - GANs - Generating new worlds
- 02 - What you should know
1. Origin and Examples of GANs
- 03 - Introduction to GANs
- 04 - Origin - Where did they come from
- 05 - How were they developed
- 06 - Early examples of GANs
2. Architecture and Training Methods
- 07 - Model architecture
- 08 - Training method
- 09 - How the different models learn
- 10 - Final model output
3. Training a Model
- 11 - Create a basic GAN
- 12 - Start training and compare results
4. The Future of Generative AI
- 13 - Where generative AI has moved to
- 14 - Where generative AI will move to