Learn Generative AI with PyTorch

designed for those who have a good grasp of Python and a basic

understanding of machine learning, particularly neural networks. It aims to

guide you through the creation of generative models from the ground up.

This book is born out of my journey in building and

understanding these models from scratch. It's the book I wish I had during my

experiments with various generative models. It begins with simple models,

helping readers build foundational deep learning skills before advancing to

more complex challenges. I chose PyTorch for its dynamic computational

graph and clear syntax after experimenting with TensorFlow.

All generative models in this book are deep neural networks. The book starts

with a comprehensive deep learning project in PyTorch, ideal for those new

to the field. Each chapter is carefully structured to build upon the previous

one, especially beneficial for readers new to deep learning in PyTorch. You'll

start by creating basic content like shapes, numbers, and images using

Generative Adversarial Networks (GANs) with straightforward architectures.

As you progress, the complexity increases, culminating in building advanced

models like Transformers.