@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…

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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。

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…
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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.

CoverDetails
AI Agents in ActionAI 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 EngineeringAI 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 ModelBuild 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 ApplicationsBuilding 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 ProductionBuilding 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 LLMsCreating 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 ChatGPTDeveloping 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 AWSGenerative 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 LangChainGenerative 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 ModelsHands-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 CourseLangChain 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 ModelsLarge 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 HandbookLLM 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 ProductionLLMs 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 TransformersNatural 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 AIPrompt 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 LLMsPrompt 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 ModelsQuick 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 AIRAG-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 GuideSuper 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 BibleThe 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 SecurityThe 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 BookThe 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…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:

  1. Create a master list of all known books on LLM development (amazon, goodreads, google books, etc.)
  2. Read book blurb and table of contents to confirm relevance (for “engineers doing LLM development”).
  3. Read reviews and check star ratings for quality (quality check).
  4. Read comments and discussion about the book on social (twitter/reddit/etc).
  5. Acquire the ebook version of the book, if possible (final read/skim to confirm relevance and quality).
  6. 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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This tweet introduces 'Awesome LLM Books', a curated GitHub list of 22 high-quality books for LLM development, evaluated by strict criteria including relevance, content quality, and social proof. Each book entry includes author, publisher, rating, and links, helping developers quickly find suitable resources.