"Hands-On Large Language Models: Language Understanding and Generation" is an illustrated guide for Python developers, co-authored by Jay Alammar and Maarten Grootendorst. Through more than 275 custom illustrations and runnable code, the book systematically introduces the core concepts and practical applications of large language models (LLMs).
According to official materials, the book covers LLM construction techniques, generation, representation, and retrieval applications, including cutting-edge technologies such as Transformer models, tokenizers, semantic search, and RAG. The book starts with a simple introduction and gradually goes deeper, ultimately guiding readers to confidently fine-tune and build their own large language models.
Author Jay Alammar is an engineering researcher and director at Cohere, and his AI blog has helped millions of researchers and engineers visually understand machine learning tools and concepts; Maarten Grootendorst is a senior clinical data scientist at IKNL, holds master's degrees in psychology and data science, and is the author and maintainer of open-source packages such as BERTopic, PolyFuzz, and KeyBERT.
The book has been recommended by many industry experts, including the founder of DeepLearning.AI and the machine learning director at Cohere, who praise its beautiful illustrations, practical code, and clear explanations, making it an important resource for understanding LLMs.
In terms of usage, the book provides Python code examples, and readers can learn through practice. Applicable scenarios include researchers, engineers, and data scientists who want to understand LLMs, as well as anyone interested in the latest AI technologies. In terms of limitations, the book is mainly aimed at Python developers and requires a certain programming foundation.
