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.

Build GPT-2, Llama 3, and DeepSeek from scratch in PyTorch. Every chapter has runnable end-to-end code and loads real pretrained weights. Goes well past where most LLM tutorials stop.

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.

if you've read my chapter on naming in a famous software book (first or second edition) you may want to go a little deeper. Same author, same topic, all-new content!

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.

위성은 매일 방대한 양의 이미지를 수집하지만, 픽셀을 통찰로 바꾸기 위해서는 AI가 필요합니다. 이 책은 Python과 오픈소스 도구를 사용하여 실제 위성 이미지에 딥러닝 모델을 구축, 학습, 적용하는 방법을 알려줍니다. 지금 바로 실행할 수 있는 코드로 구성된 23개의 장을 포함하고 있으며, 모든 코드 예제는 https://book.opengeoai.org 에서 무료로 제공됩니다.

Master machine learning interpretability with this comprehensive guide to SHAP – your tool to communicating model insights and building trust in all your machine learning applications.

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

You know how to program in Python but are interested in what goes on under the covers of the interpreter? Well, fasten your seat-belts as this book will take you on a tour of  the virtual machine that runs your Python code. It will describe how Python code is compiled and run, how the language itself can be modified and will demystify the mysterious bytecodes that run on the Python virtual machine.

Stop Watching the Market. Start Coding It. 📈 Welcome to the era of "Quantamental" AI Trading. Volume 7 is your engineering manual for building professional-grade trading infrastructure. Bridge the gap between classical technical analysis and LLMs—designing systems that trade on both Math (price action) and News (sentiment). From vectorized backtesting to sentiment analysis with FinBERT, it’s time to engineer your edge.

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.

Desbloquea el poder de DuckDB para la analítica geoespacial moderna. Esta guía práctica ayuda a los profesionales de SIG a dominar la gestión eficiente de datos espaciales, transformando grandes conjuntos de datos del mundo real en conocimientos valiosos mediante SQL, Python y la extensión espacial de DuckDB. La edición impresa a todo color está disponible en Amazon.

Libérez la puissance des données géospatiales avec Python ! Ce guide pratique s’adresse aux débutants et utilisateurs intermédiaires désireux d’explorer l’analyse spatiale et la cartographie interactive à l’aide d’outils open source. Grâce à des exemples concrets et des données réelles, vous apprendrez à manipuler des données spatiales, à programmer en Python, à analyser des données vectorielles et matricielles, à créer des cartes web interactives, et à utiliser le cloud computing. Étudiant, chercheur, professionnel des SIG ou data scientist : ce livre vous donnera les outils pour relever les défis géospatiaux avec assurance.

Unlock the power of geospatial data with Python! This hands-on guide is designed for beginners and intermediate users eager to explore spatial analysis and interactive mapping using open-source tools. You'll learn how to work with real-world data through practical examples and build skills in Python programming, vector and raster analysis, web mapping, and cloud computing. Whether you're a student, researcher, GIS professional, or data scientist, this book will equip you with the tools to tackle geospatial challenges with confidence. Color-print copies are available through Amazon.

Get started quickly, creating applications for the Model Context Protocol (MCP) using the official MCP SDKs for Python, Java 21, and Node.js. Quickly master, all of the concepts needed in order to build MCP servers, including transport protocols, tools, resources, prompts, roots, and sampling. Learn how to get familiar with popular MCP client applications such as, Claude Desktop, Postman, and the MCP Inspector.