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.

Mastering Modern Time Series Forecasting is your all-in-one guide to building real-world forecasting systems that work — from classical stats to deep learning and beyond. Whether you're modeling retail demand or energy loads, this book gives you the tools, intuition, and code to go from zero to production. You'll cover ARIMA, ML, deep nets, transformers, and even the rise of FTSMs (Foundational Time Series Models). Written by a practitioner who’s built forecasting solutions for multibillion-dollar businesses, this is the hands-on, honest guide every data scientist, analyst, or forecaster needs.

Unlock the power of DuckDB for modern geospatial analytics. This hands-on guide helps GIS professionals master efficient spatial data management, transforming massive real-world datasets into powerful insights using SQL, Python, and DuckDB’s spatial extension. Full-color print edition is available on Amazon.

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.

Learn how large language models work by building one from scratch. This hands-on guide walks you from first principles to a working Transformer you understand inside out.

日本語テキストを処理したい全てのプログラマ・エンジニアの方へ。分かち書きなどの基本から、自然言語生成などの最新の話題までをカバー。動かして学べるコードや、参照文献も付いています。言語学や機械学習の知識が無くても問題ありません。

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.

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.

The book contains the full transcript of Software Diagnostics Services training with 10 hands-on exercises on various topics related to Windows API.

The book contains the full transcript of Software Diagnostics Services training with 25 hands-on exercises. This training course extends pattern-oriented analysis introduced in Accelerated Windows Memory Dump Analysis, Accelerated .NET Core Memory Dump Analysis, and Advanced Windows Memory Dump Analysis with Data Structures.

Turn uncertainty into a competitive advantage with probabilistic forecasting and Conformal Prediction.

Are you a data scientist or analyst struggling to take your Jupyter Notebook prototypes to the next level? Have you encountered challenges with code organization, reproducibility, or collaboration as your data science projects grow in complexity? This book is the solution you’ve been seeking. This comprehensive guide bridges the gap between data analysis and software engineering, providing you with the essential tools and best practices to transform your data science projects into scalable, maintainable, and collaborative solutions.

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.

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 how to apply Large Language Models (LLMs) to real-world financial data. This book walks you through sentiment analysis, RAG pipelines, and trading strategies using Python and modern AI tools.