Building your first GAN in Python

Offered By
Coursera Project Network
In this Guided Project, you will:

Understand concepts behind the training of GANs

Code the Generator and Discriminator components of a GAN using Tensorflow in Python

Code and run the training loop of a GAN using Tensorflow in Python

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

By the end of this project, you will have learned the basics behind designing and coding Generative Adversarial Networks, or GANs. This project will familiarize you with concepts and techniques at work behind the scenes in GANs and deepfakes. The methods you will learn in the course of this project will enable you to build Generative Adversarial Networks for any potential purpose and provide valuable experience in your Machine Learning and Artificial Intelligence development journey. Python experience is heavily recommended. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

TensorflowPython ProgrammingGenerative Models

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Exploring GANs

  2. Coding a Generator Network

  3. Coding the Discriminator Component

  4. Coding the Training Function

  5. Running the Training, and Discussing the Future

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.