This repository is a curated list of books for engineers focused on developing with Large Language Models (LLMs). It aims to provide a high-quality, filtered selection of resources, saving developers time in identifying relevant and well-regarded literature on LLM engineering, application development, and production deployment.

How It Works

The list is meticulously curated through a multi-stage process. It begins with a broad collection of LLM-related books, which are then filtered based on relevance to "engineers doing LLM development" by examining blurbs and tables of contents. A quality check is performed using Amazon and Goodreads star ratings, supplemented by social media discussions. The final stage involves an optional acquisition and review of the ebook for a definitive relevance and quality assessment.

Quick Start & Requirements

This is a curated list, not a software project. No installation or execution is required.

Highlighted Details

• Books cover a range of topics including AI engineering, building LLMs from scratch, production deployment, prompt engineering, and security.
• Includes star ratings from Amazon and Goodreads for each book, offering a quantitative measure of quality.
• Provides direct links to purchase, publisher pages, and GitHub projects where available.
• The list is actively maintained, with updates based on new publications and community feedback.

Maintenance & Community

The list is maintained by Jason Brownlee. Suggestions for improving the list can be sent via email to Jason.Brownlee05@gmail.com.

Licensing & Compatibility

This repository contains a list of external resources and is not subject to software licensing. The books themselves are subject to their respective publisher's licenses.

Limitations & Caveats

The curation process involves subjective judgment, and the list is not exhaustive, focusing specifically on resources deemed relevant for engineers. Star ratings are periodically updated and may not reflect the absolute latest reviews.