Hands-On Large Language Models provides a practical introduction to building, fine-tuning, and deploying large-scale AI language models. Covering foundational concepts in natural language processing (NLP), the book walks readers through the latest advancements in transformer-based architectures like GPT, BERT, and T5. Through hands-on coding examples, the authors demonstrate how to train, optimize, and integrate LLMs into real-world applications, ensuring efficiency, scalability, and responsible AI usage.

Why Read This Book

• Learn the fundamentals of large language models, including transformers and attention mechanisms.
• Explore cutting-edge models like GPT, BERT, and T5 with real-world applications.
• Gain hands-on experience with fine-tuning, inference optimization, and deployment strategies.
• Understand ethical considerations and best practices for responsible AI.
• Written by Jay Alammar, known for his clear visual explanations of AI, and Maarten Grootendorst, an expert in NLP.

About the Authors

Jay Alammar is a data scientist, educator, and AI researcher known for his widely popular visual guides explaining machine learning concepts, particularly transformer models. His work simplifies complex AI topics for a broad audience.

Maarten Grootendorst is a machine learning researcher specializing in NLP. He is the creator of BERTopic, an advanced topic modeling framework that leverages transformer-based embeddings, and has contributed extensively to the field of applied AI.