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  1. Mastering Modern Time Series Forecasting
    A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python (Preorder)
    Valery Manokhin

    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.

  2. Spatial Data Management with DuckDB
    From SQL Basics to Advanced Geospatial Analytics
    Qiusheng Wu

    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.

  3. Introduction to GIS Programming
    A Practical Python Guide to Open Source Geospatial Tools
    Qiusheng Wu

    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.

  4. Production Ready Data Science
    From Prototyping to Production with Python
    Khuyen Tran

    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.

  5. Build Your First LLM
    A Hands-On Guide to Language Models
    Hasan Degismez

    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.

  6. Introduction to Japanese Natural Language Processing
    Masato Hagiwara and Paul O'Leary McCann

    A thorough guide for programmers working with Japanese text, covering fundamental issues like tokenization and recent research topics like generating natural language texts. Working examples are accompanied by extensive reference to allow problem solving even without a background in Japanese or Machine Learning.

  7. Discrete Mathematics for Computer Science
    Alexander S. Kulikov, Alexander Golovnev, Alexander Shen, Vladimir Podolskii, and Marie Brodsky

    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.

  8. From Source Code To Machine Code
    Build Your Own Compiler From Scratch
    build-your-own.org

    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.

  9. Introducción a la Programación GIS
    Una Guía Práctica de Python para Herramientas Geoespaciales de Código Abierto
    Qiusheng Wu

    ¡Desbloquea el poder de los datos geoespaciales con Python! Esta guía práctica está diseñada para principiantes y usuarios intermedios que desean explorar el análisis espacial y la cartografía interactiva utilizando herramientas de código abierto. Aprenderás a trabajar con datos del mundo real a través de ejemplos prácticos y desarrollarás habilidades en programación con Python, análisis vectorial y ráster, mapeo web y computación en la nube. Ya seas estudiante, investigador, profesional GIS o científico de datos, este libro te proporcionará las herramientas necesarias para enfrentar con confianza los desafíos geoespaciales.

  10. L'Impresa Cibernetica (Edizione Italiana)
    Come Costruire un'Organizzazione Pronta per il Futuro
    Romano Roth and TranslateAI

    La maggior parte delle imprese può fornire risultati velocemente, ma poche sanno adattarsi su larga scala.L'Impresa Cibernetica introduce un modello operativo unificante che incorpora l'IA, i cicli di feedback e il pensiero orientato alle piattaforme nel DNA della vostra organizzazione. Scoprite come costruire un sistema che percepisce il cambiamento, apprende continuamente e trasforma le disruption in vantaggio strategico.

  11. The Cybernetic Enterprise
    How to Build a Future-Ready Organization
    Romano Roth

    Most enterprises can deliver fast, but few can adapt at scale.The Cybernetic Enterprise introduces a unifying operating model that embeds AI, feedback loops, and platform thinking into the DNA of your organization. Learn how to build a system that senses change, learns continuously, and transforms disruption into strategic advantage.

  12. Interpreting Machine Learning Models With SHAP
    A Guide With Python Examples And Theory On Shapley Values
    Christoph Molnar

    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.

  13. Creating AI Agents with MCP - Model Context Protocol
    Part of the series, "The Only Book You'll Need On..."
    Lydia Evelyn and Bruce Hopkins

    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.

  14. Implementing the Clean Architecture
    Python Edition
    Sebastian Buczyński

    Learn how to apply the Clean Architecture. The book strongly focuses on practical aspects and is illustrated with tons of code snippets. Code samples are in Python.

  15. The Augmented Developer
    Code Smarter, Not Harder
    Aymen El Amri

    A Developer’s Practical Guide to AI-Driven Productivity