Generative Adversarial Networks (GANs): Complete Guide Course
Deep Learning and Computer Vision to implement projects using one of the most revolutionary technologies in the world!
GANs (Generative Adversarial Networks) are considered one of the most modern and fascinating technologies within the field of Deep Learning and Computer Vision. They have gained a lot of attention because they can create fake content. One of the most classic examples is the creation of people who do not exist in the real world to be used to broadcast television programs. This technology is considered a revolution in the field of Artificial Intelligence for producing high quality results, remaining one of the most popular and relevant topics.
In this course you will learn the basic intuition and mainly the practical implementation of the most modern architectures of Generative Adversarial Networks! This course is considered a complete guide because it presents everything from the most basic concepts to the most modern and advanced techniques, so that in the end you will have all the necessary tools to build your own projects! See below some of the projects that you are going to implement step by step.
What you’ll learn
- Understand the basic intuition about GANs
- Generate images of digits (0 – 9) using DCGAN and WGAN
- Transform satellite images into maps using Pix2Pix architecture
- Transform zebras into horses using CycleGAN architecture
- Transfer styles between images
- Apply super resolution to improve image quality using ESRGAN architecture
- Create new faces of people with high quality and definition using StyleGAN
- Generate images through textual descriptions
- Restore old photos using GFP-GAN
- Complete missing parts of images using Boundless architecture
- Generate deepfakes to swap faces with SimSwap
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