Deep Learning with PyTorch Step-by-Step: A Beginner's Guide: Volume III: Sequences & NLP

This book is a comprehensive guide to learning PyTorch for deep learning and sequence-related models, including recurrent neural networks, sequence-to-sequence models, attention, self-attention, and transformers.

The author takes an easy-to-follow, structured, incremental, and from-first-principles approach to learning PyTorch, making it accessible to readers of all skill levels.

The book includes a crash course on natural language processing (NLP) and covers popular models such as BERT and GPT-2 using the HuggingFace library.

With this book, you'll gain a thorough understanding of the concepts and tools necessary to develop, train, and fine-tune language models using PyTorch.

Whether you're a beginner or an experienced deep learning practitioner, this book is sure to provide valuable insights and practical knowledge that will help you master PyTorch for sequence-related models.