Make Your First GAN Using PyTorch

A gentle introduction to Generative Adversarial Networks, and a practical step-by-step tutorial on making your own with PyTorch.

• Pytorch basics
• Making a neural network with PyTorch
• Refining the neural network output
• Basics of CUDA
• The basic idea of GAN
• Learning a simple 1010 pattern using GAN
• Learning handwritten digits using GAN
• Learning human faces using GAN
• Convolutional GANs
• Conditional GANs

This course is an introduction to Generative Adversarial Networks (GANs) and a practical step-by-step tutorial on making your own with PyTorch. Through this course, you will learn how to build GANs with industry-standard tools.

In the first section, you will dive into PyTorch and refresh your understanding of neural networks by building a simple image classifier. 

In the second section of this course, you will explore the idea of adversarial training and build progressively more sophisticated GANs; first by learning a simple 1010 pattern, then monochrome images of handwritten digits, and finally full-color images of faces.

The third, and last section, extends the core GAN concept, applying it to convolutional neural networks, and developing a conditional GAN for generating data of the desired class.

By the end of this course, you will have a solid understanding of how to build GANs for your machine learning projects.