Preface

"Imagination is more important than knowledge."

– Albert Einstein, Einstein on Cosmic Religion and Other Opinions and Aphorisms (2009)

In this book we will explore generative AI, a cutting-edge technology for generating synthetic (yet strikingly realistic) data using advanced machine learning algorithms. Generative models have been intriguing researchers across domains for quite some time now. With recent improvements in the fields of machine learning and more specifically deep learning, generative modeling has seen a tremendous uptick in the number of research works and their applications across different areas. From artwork and music composition to synthetic medical datasets, generative modeling is pushing the boundaries of imagination and intelligence alike. The amount of thought and effort required to understand, implement, and utilize such methods is simply amazing. Some of the newer methods (such as GANs) are very powerful, yet difficult to control, making the overall learning process both exciting and frustrating.

Generative AI with Python and TensorFlow 2 is the result of numerous hours of hard work by us authors and the talented team at Packt Publishing to help you understand this deep, wide, and wild space of generative modeling. The aim of this book is to be a kaleidoscope of the generative modeling space and cover a wide range of topics. This book takes you on a journey where you don't just read the theory and learn about the fundamentals, but you also discover the potential and impact of these models through worked examples. We will implement these models using a variety of open-source technologies – the Python programming language, the TensorFlow 2 library for deep neural network development, and cloud computing resources such as Google Colab and the Kubeflow project.

Having an understanding of the various topics, models, architectures, and examples in this book will help you explore more complex topics and cutting-edge research with ease.