@Huahuazo: 市面上LLM相关的书单多如牛毛,但真正值得花时间翻阅的究竟有几本?一位资深开发者已经替你蹚过了这道浑水。 他维护了一份名为Awesome LLM Books的精选书单,用六项硬性指标对候选书籍进行了残酷筛选——主题契合度、内容质量、读者口…
摘要
一位资深开发者维护的Awesome LLM Books精选书单,收录22本高质量LLM相关书籍,覆盖从入门到进阶的核心学习路径,附有详细评分和链接。
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市面上LLM相关的书单多如牛毛,但真正值得花时间翻阅的究竟有几本?一位资深开发者已经替你蹚过了这道浑水。
他维护了一份名为Awesome LLM Books的精选书单,用六项硬性指标对候选书籍进行了残酷筛选——主题契合度、内容质量、读者口碑都在考核范围内,但凡有短板就直接出局。
这份书单目前收录了22本高质量著作,清晰覆盖了从入门到进阶的几条核心学习路径:基础理论、模型构建、应用开发、提示工程,以及生成与部署。
每本书都附有详细的作者、出版社、各大平台评分和直达链接,让你一眼就能判断这本书是否值得投入时间去啃。
https://github.com/Jason2Brownlee/awesome-llm-books…
Jason2Brownlee/awesome-llm-books
Source: https://github.com/Jason2Brownlee/awesome-llm-books
Awesome LLM Books
Some of us learn best by reading high quality books on technical topics.
This is a curated list of books for engineers on development with Large Language Models (LLMs).
Books:
Alphabetical list of books on LLMs. Each cover/title links to more information about the book.
| Cover | Details |
|---|---|
![]() | AI Agents in Action Authors: Micheal Lanham Publisher: Manning, 2025 Star Rating: 4.1 on Amazon, 3.3 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | AI Engineering Subtitle: Building Applications with Foundation Models Authors: Chip Huyen Publisher: O’Reilly, 2025 Star Rating: 4.7 on Amazon, 4.46 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Build a Large Language Model Subtitle: (From Scratch) Authors: Sebastian Raschka Publisher: Manning, 2024 Star Rating: 4.6 on Amazon, 4.62 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Building LLM Powered Applications Subtitle: Create intelligent apps and agents with large language models Authors: Valentina Alto Publisher: Packt, 2024 Star Rating: 4.2 on Amazon, 3.54 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Building LLMs for Production Subtitle: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG Authors: Louis-François Bouchard and Louie Peters Publisher: Independently published, 2024 Star Rating: 4.4 on Amazon, 4.10 on Goodreads Links: Amazon, Goodreads, Publisher |
![]() | Creating Production-Ready LLMs Subtitle: A Comprehensive Guide to Building, Optimizing, and Deploying Large Language Models for Production Use Authors: TransformaTech Institute Publisher: Independently published, 2024 Star Rating: 4.3 on Amazon, 0.00 on Goodreads Links: Amazon, Goodreads, Publisher |
![]() | Developing Apps with GPT-4 and ChatGPT Subtitle: Build Intelligent Chatbots, Content Generators, and More Authors: Olivier Caelen and Marie-Alice Blete Publisher: O’Reilly, 2023 Star Rating: 4.1 on Amazon, 3.67 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Generative AI on AWS Subtitle: Building Context-Aware Multimodal Reasoning Applications Authors: Chris Fregly, Antje Barth and Shelbee Eigenbrode Publisher: O’Reilly, 2023 Star Rating: 4.4 on Amazon, 4.33 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Generative AI with LangChain Subtitle: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs Authors: Ben Auffarth Publisher: Packt, 2023 Star Rating: 4.3 on Amazon, 3.58 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Hands-On Large Language Models Subtitle: Language Understanding and Generation Authors: Jay Alammar and Maarten Grootendorst Publisher: O’Reilly, 2024 Star Rating: 4.7 on Amazon, 4.33 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | LangChain Crash Course Subtitle: Build OpenAI LLM powered Apps: Fast track to building OpenAI LLM powered Apps using Python Authors: Greg Lim Publisher: Independently Published, 2024 Star Rating: 4.1 on Amazon, 4.00 on Goodreads Links: Amazon, Goodreads, Publisher |
![]() | Large Language Models Subtitle: A Deep Dive: Bridging Theory and Practice Authors: Uday Kamath, Kevin Keenan, Garrett Somers, and Sarah Sorenson Publisher: Springer, 2024 Star Rating: 4.4 on Amazon, 4.33 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | LLM Engineer’s Handbook Subtitle: Master the art of engineering large language models from concept to production Authors: Paul Iusztin and Maxime Labonne Publisher: Packt, 2024 Star Rating: 4.6 on Amazon, 3.85 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | LLMs in Production Subtitle: From language models to successful products Authors: Christopher Brousseau and Matthew Sharp Publisher: Manning, 2025 Star Rating: 4.6 on Amazon, 4.05 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Natural Language Processing with Transformers Subtitle: Building Language Applications with Hugging Face Authors: Lewis Tunstall, Leandro von Werra and Thomas Wolf Publisher: O’Reilly, 2022 Star Rating: 4.6 on Amazon, 4.39 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Prompt Engineering for Generative AI Subtitle: Future-Proof Inputs for Reliable AI Outputs Authors: James Phoenix and Mike Taylor Publisher: O’Reilly, 2024 Star Rating: 4.5 on Amazon, 3.62 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Prompt Engineering for LLMs Subtitle: The Art and Science of Building Large Language Model–Based Applications Authors: John Berryman and Albert Ziegler Publisher: O’Reilly, 2024 Star Rating: 4.1 on Amazon, 4.29 on Goodreads Links: Amazon, Goodreads, Publisher |
![]() | Quick Start Guide to Large Language Models Subtitle: Strategies and Best Practices for ChatGPT, Embeddings, Fine-Tuning, and Multimodal AI Authors: Sinan Ozdemir Publisher: Addison-Wesley, 2024 Star Rating: 4.4 on Amazon, 3.64 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | RAG-Driven Generative AI Subtitle: Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone Authors: Denis Rothman Publisher: Packt, 2024 Star Rating: 4.1 on Amazon, 3.72 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | Super Study Guide Subtitle: Transformers & Large Language Models Authors: Afshine Amidi and Shervine Amidi Publisher: Independently published, 2024 Star Rating: 4.6 on Amazon, 4.62 on Goodreads Links: Amazon, Goodreads, Publisher |
![]() | The Agentic AI Bible Subtitle: The Complete and Up-to-Date Guide to Design, Build, and Scale Goal-Driven, LLM-Powered Agents that Think, Execute and Evolve Authors: Thomas R. Caldwell Publisher: Independently published, 2025 Star Rating: 4.7 on Amazon, 3.67 on Goodreads Links: Amazon, Goodreads |
![]() | The Developer’s Playbook for Large Language Model Security Subtitle: Building Secure AI Applications Authors: Steve Wilson Publisher: O’Reilly, 2024 Star Rating: 4.7 on Amazon, 3.86 on Goodreads Links: Amazon, Goodreads, Publisher |
![]() | The Hundred-Page Language Models Book Subtitle: Hands-on with PyTorch Authors: Andriy Burkov Publisher: True Positive Inc., 2025 Star Rating: 4.8 on Amazon, 4.5 on Goodreads Links: Amazon, Goodreads, Publisher, GitHub Project |
![]() | What Is ChatGPT Doing… Subtitle: …and Why Does It Work? Authors: Stephen Wolfram Publisher: Wolfram Media Inc., 2023 Star Rating: 4.2 on Amazon, 3.86 on Goodreads Links: Amazon, Goodreads, Publisher |
On Curation
The above list is not “all books on LLM development”, instead it is filtered using the following procedure:
- Create a master list of all known books on LLM development (amazon, goodreads, google books, etc.)
- Read book blurb and table of contents to confirm relevance (for “engineers doing LLM development”).
- Read reviews and check star ratings for quality (quality check).
- Read comments and discussion about the book on social (twitter/reddit/etc).
- Acquire the ebook version of the book, if possible (final read/skim to confirm relevance and quality).
- Final judgement call (publisher, gut check).
Note that I update the list based on newly published books and emails I received about new books. Additionally, listed star ratings are updated periodically.
Make The List Better
Do you have ideas on how we make this list more awesome?
Email any time: [email protected]
Disclaimer: As an Amazon Associate I earn from qualifying purchases. This means that when you buy through my links, I may earn a commission.
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