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.
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