Apply Generative Adversarial Networks (GANs)

DeepLearning.AI via Coursera

Coursera based on 544 ratings

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Overview

In this course, you will: - Explore the applications of GANs and examine them wrt data augmentation, privacy, and anonymity - Leverage the image-to-image translation framework and identify applications to modalities beyond images - Implement Pix2Pix, a paired image-to-image translation GAN, to adapt satellite images into map routes (and vice versa) - Compare paired image-to-image translation to unpaired image-to-image translation and identify how their key difference necessitates different GAN architectures - Implement CycleGAN, an unpaired image-to-image translation model, to adapt...

Syllabus

Week 1: GANs for Data Augmentation and Privacy

Learn different applications of GANs, understand the pros/cons of using them for data augmentation, and see how they can improve downstream AI models!

Week 2: Image-to-Image Translation with Pix2Pix

Understand image-to-image translation, learn about different applications of this framework, and implement a U-Net generator and Pix2Pix, a paired image-to-image translation GAN!

Week 3: Unpaired Translation with CycleGAN

Understand how unpaired image-to-image translation differs from paired translation, learn how CycleGAN implements this model using two GANs, and implement a CycleGAN to transform between horses and zebras!