Books

This book is specially written for ML engineers who know what a groupby is but want to know why it's slow and how to fix it; data scientists who understand sentiment analysis but want to see how it connects cleanly to a Pandas pipeline; and data engineers who ship Pandas code to production and need to know which patterns will break on Pandas 3.0 and which are safe.

Master the engineering principles behind Unsloth to fine-tune Large Language Models on limited hardware. Discover technical workflows for 4-bit quantization, custom Triton kernels, and Direct Preference Optimization. This guide covers the full lifecycle, including context expansion and production deployment via GGUF and vLLM. A rigorous reference for developers seeking to maximize LLM performance on consumer-grade GPUs.

Python Engineering Judgment is for engineers who already know Python and want to build the skill AI makes more valuable: the ability to reason about code, systems, tradeoffs, and failure modes. This deep, practical field guide teaches the Python object model, type system, decorators, generators, concurrency, asyncio, multiprocessing, API design, packaging, performance, debugging, security, observability, and reliability through the lens of real-world engineering judgment. Use it to prepare for senior, staff, principal, and tech-lead interviews, and to make better decisions in code reviews and production systems.

Most books about ChatGPT explain the magic. This one shows you the math. Inside Large Language Models, Volume I takes a curious beginner from "what is an LLM" to a complete, trained GPT, with nothing more than high-school algebra, a working laptop, and a willingness to read carefully. Every formula is walked through by hand. Every line of code comes with a plain-English explanation. By the end you will have built, trained, and run your own transformer from scratch, and you will know exactly what is happening inside. No PhD or Data Science required. No prior machine learning needed. Just curiosity and a calculator.

Most books about ChatGPT explain the magic. This one shows you the math. Inside Large Language Models, Volume I takes a curious beginner from "what is an LLM" to a complete, trained GPT, with nothing more than high-school algebra, a working laptop, and a willingness to read carefully. Every formula is walked through by hand. Every line of code comes with a plain-English explanation. By the end you will have built, trained, and run your own transformer from scratch, and you will know exactly what is happening inside. No PhD or Data Science required. No prior machine learning needed. Just curiosity and a calculator.

Working with PySide6 should not depend on trial and error. This book replaces fragmented learning with a structured approach, combining in-depth explanations and dependable code examples that move you forward with confidence.

跳过黑箱框架。用纯 Python 从零构建生产级 AI 编程智能体——云端或本地，用 pytest 测试，全部在一个文件中完成。

Olvídate de los frameworks de caja negra. Construye un agente de programación de IA de nivel profesional desde cero en Python puro — en la nube o local, probado con pytest, todo en un solo archivo.

ブラックボックスのフレームワークは不要。純粋なPythonでプロダクションレベルのAIコーディングエージェントをゼロから構築。クラウドでもローカルでも、pytestでテスト済み、すべて1つのファイルに収まります。

Learn Polars, the pandas killer for data analysis.

The best compliment a reader can pay your code is not "this is impressive" — it is "this was exactly what I expected." Beautiful but Boring teaches the discipline of writing Python that earns that compliment: precise naming contracts, type annotations that say what a function actually requires, and a framework for maintaining those standards consistently across a codebase, a team, and a career.

The recipes in this book are practical answers to the kind of problems that real Django applications encounter, sometimes on the first day of a project and sometimes deep into the life of a codebase that has grown well beyond its original design. This book is written to guide you to utilize Django 6.0 capabilities in your apps with ease of implementation.

Learn LangGraph the fast, practical way by building real projects from your very first chapter. This hands-on guide cuts out the fluff and walks you step-by-step from simple graphs to powerful AI agents like ReAct and RAG. If you prefer learning by doing, this book will get you up and running quickly without overwhelming you.

Master AWS IoT Core with this hands-on, comprehensive guide. Learn how to securely connect, manage, and scale your IoT device fleets using MQTT, AWS IoT Greengrass, bulk enrollments, and OTA updates. From edge hardware setups to cloud analytics and Zero Trust security, build enterprise-grade architectures today.

Satélites capturam enormes volumes de imagens todos os dias, mas transformar pixels em conhecimento requer IA. Este livro ensina você a construir, treinar e aplicar modelos de aprendizado profundo a imagens de satélite reais usando Python e ferramentas de código aberto, com 23 capítulos de código executável que você pode usar hoje mesmo. Todos os exemplos de código estão disponíveis gratuitamente em https://book.opengeoai.org.