Books

Skip the black-box frameworks. Build a production-grade AI coding agent from scratch in pure Python - cloud or local, tested with pytest, all in a single file.

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.

This book supplements the DM for CS Specialization at Coursera and contains many interactive puzzles, autograded quizzes, and code snippets. They are intended to help you to discover important ideas in discrete mathematics on your own. By purchasing the book, you will get all updates of the book free of charge when they are released.

800 pages. 11 chapters. The full forecasting stack in Python — from ARIMA to foundation models — with production-grade code and proper evaluation. No hype.

Pull a model onto a machine you own, shape it with a Modelfile, fine-tune your own adapter, and build a chat app that calls tools and talks to an MCP server, all running on your own hardware. By the end, you'll know exactly where owning your AI beats renting it, and where it doesn't.

Learn Claude Code by building real projects. This hands-on companion turns the Claude Code Masterclass workshop into a practical self-paced guide for planning, coding, testing, reviewing, refactoring, and shipping software with AI.

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.

Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples.

Bad data breaks good code. You’ve written Python that works perfectly in testing, only to watch it fail in production because of a malformed API request, a messy CSV, or a missing config value. That’s the hidden cost of Python’s flexibility: without runtime validation, you’re always one bad input away from a crash. Enter Pydantic. This book takes you from the foundations of data validation to real-world applications in APIs, data pipelines, configurations, and machine learning workflows. Along the way, you’ll explore practical techniques, advanced features, and alternatives like Marshmallow, attrs, and dataclasses, so you’ll always know which tool is right for the job. If you’re a Python developer, data engineer, or FastAPI user, this is your roadmap to writing safer, cleaner, and more reliable code.

Our goal with this book is to give you a practical and thorough introduction to the Python programming language, providing you with the tools and insight you need to be a productive Python developer. We want to help you build solid foundations, orient you in the universe of Python, and put you in a position to direct your own continued learning.

A beginner-friendly introduction to machine learning with Python, that is based on the PyCaret and Streamlit libraries. Readers will delve into the fascinating world of artificial intelligence, by easily training and deploying their ML models!

卫星每天获取海量影像数据，但将像素转化为洞察需要借助人工智能。本书将教你如何使用 Python 和开源工具构建、训练并应用深度学习模型，处理真实的卫星影像。全书包含 23 个可运行的代码章节，帮助你即学即用。所有代码示例均可在 https://book.opengeoai.org 免费获取。

Satellites capture massive volumes of imagery every day, but turning pixels into insight requires AI. This book teaches you to build, train, and apply deep learning models to real satellite imagery using Python and open-source tools, with 23 chapters of executable code you can run today. All code examples are freely availabe at https://book.opengeoai.org.

Build and operate production AI platforms on Kubernetes. Learn to manage NVIDIA GPUs, serve and optimize LLMs with vLLM, run training and batch workloads, and design secure, observable, multi-tenant infrastructure for AI at scale.

Build a compiler to learn how programming languages work. Use low-level assembly to learn how computers work. Walks through a minimal yet complete compiler. Compiles a static-typed language into x64 ELF executables.Simple interpreter.Bytecode compiler.x64 assembly & instruction encoding.Translate bytecode to x64 code.Generate binary executables.