Preface

The book will start from the theoretical foundations of deep neural networks (NN), and it will delve into the most popular network architectures – transformers, transformer-based large language models (LLMs), and convolutional networks. It will introduce these models in the context of various computer vision and natural language processing (NLP) examples, including state-of-the-art applications such as text-to-image generation and chatbots.

Each chapter is organized with a comprehensive theoretical introduction to the topic as its main body. This is followed by coding examples that serve to validate the presented theory, providing readers with practical hands-on experience. The examples are executed using PyTorch, Keras, or Hugging Face Transformers.