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  1. Das kybernetische Unternehmen (Deutsche Ausgabe)
    Das kybernetische Unternehmen (Deutsche Ausgabe)
    So bauen Sie eine zukunftsfähige Organisation auf
    Romano Roth and TranslateAI

    Die meisten Unternehmen können schnell liefern, aber nur wenige können sich in großem Maßstab anpassen.The Cybernetic Enterprise stellt ein einheitliches Betriebsmodell vor, das KI, Rückkopplungsschleifen und Plattform-Denken in die DNA Ihrer Organisation einbettet. Erfahren Sie, wie Sie ein System aufbauen, das Veränderungen wahrnimmt, kontinuierlich lernt und Disruption in strategische Vorteile verwandelt.

  2. Python Interview Mastery
    Python Interview Mastery
    Yotam Belgoroski

    This isn’t your typical Python interview question book. Instead of throwing random questions at you, it takes you on a journey like in a real-life interview. Starting from Python’s inner workings and building up to the practical knowledge used by experienced developers every day.Whether you’re a junior aiming to stand out with deep, beyond-your-years understanding, or a senior looking to sharpen your edge and prove your expertise, this book will prepare you to impress.

  3. A Short Guide to Naming
    A Short Guide to Naming
    Understand how and why to better name modules, classes, functions, and variables.
    Tim Ottinger

    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!

  4. The Modern Guide to AI-Powered Web Scraping and Automation
    The Modern Guide to AI-Powered Web Scraping and Automation
    Hands-On Strategies for Stealth, Structured, and AI-Driven Web Scraping
    Wasi

    Discover how modern web scraping goes beyond simple scripts. Learn to extract, automate, and transform data from dynamic websites using Python, Playwright, undetected-chromedriver, Chrome DevTools MCP, and AI tools. Packed with hands-on examples and expert tips, this book shows you how to build ethical, scalable, and intelligent scraping workflows that turn raw web content into actionable insights.

  5. Esp 32 de la A a la Z con micropython
    No Description Available
  6. Mastering Forecasting Metrics & Accuracy: For Data Science and Beyond

    Mastering Forecasting Metrics & Accuracy: For Data Science and BeyondForecasting models are only as good as the metrics used to measure them. Yet many teams still rely on outdated or misleading measures like MAPE. This book is the first comprehensive, practitioner-friendly guide dedicated entirely to forecast evaluation metrics — blending clear theory, Python recipes, and real-world case studies.Learn how to avoid common pitfalls, measure bias, handle intermittent demand, and apply advanced metrics like MASE, RMSSE, CRPS, pinball loss, and calibration scores. Each chapter includes formulas, code, and visuals to make concepts easy to apply.Perfect for data scientists, ML engineers, analysts, researchers, and industry professionals in retail, finance, and energy. No heavy math required.Living book: buy once, get free lifetime updates.Measure what matters.

  7. Mastering Forecasting Metrics & Accuracy: For Data Science and Beyond

    Mastering Forecasting Metrics & Accuracy: For Data Science and BeyondForecasting models are only as good as the metrics used to measure them. Yet many teams still rely on outdated or misleading measures like MAPE. This book is the first comprehensive, practitioner-friendly guide dedicated entirely to forecast evaluation metrics — blending clear theory, Python recipes, and real-world case studies.Learn how to avoid common pitfalls, measure bias, handle intermittent demand, and apply advanced metrics like MASE, RMSSE, CRPS, pinball loss, and calibration scores. Each chapter includes formulas, code, and visuals to make concepts easy to apply.Perfect for data scientists, ML engineers, analysts, researchers, and industry professionals in retail, finance, and energy. No heavy math required.Living book: buy once, get free lifetime updates.Measure what matters.

  8. Creating Text Adventures in Python
    Creating Text Adventures in Python
    Learn Python and Publish your Adventure on the Web
    Mike Gold

    Step inside the world where code becomes story. Creating Text Adventures in Python is your guide to building interactive fiction from scratch, even if you’re new to programming. You’ll learn how to design rooms, puzzles, and branching choices while mastering Python essentials along the way. With each chapter, your simple prototype grows into a full adventure engine—complete with item interactions, save/load systems, and web deployment so friends can play your game online. Whether you dream of crafting fantasy quests, mystery stories, or sci-fi journeys, this book shows you how to bring those worlds to life line by line. By the final page, you won’t just be reading adventures—you’ll be writing them, playing them, and sharing them with the world.

  9. Python Networking 101, Second Edition
    Python Networking 101, Second Edition
    Mastering the capability of network and socket programming, AsyncIO, network performance, simulations and Ansible
    GitforGits | Asian Publishing House

    This second edition is for Python programmers who want to get into networking but don't want to feel overwhelmed. My goal is to make you comfortable with reading code and using it to solve real-world networking problems. A lot of people wrote to me saying that it helped them automate tasks that they had been doing manually for years, while others shared how it gave them the confidence to switch careers or take on more advanced responsibilities in their roles.

  10. Practical Pydantic
    Practical Pydantic
    The Missing Guide to Data Validation in Python
    Nuno Bispo

    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.

  11. Úvod do programování GIS
    Úvod do programování GIS
    Praktický průvodce Pythonem pro open-source geoinformační nástroje
    Qiusheng Wu

    Objevte sílu geoprostorových dat s Pythonem! Tato praktická příručka je určena začátečníkům i pokročilým uživatelům, kteří chtějí proniknout do prostorové analýzy a interaktivního mapování s využitím open-source nástrojů. Naučíte se pracovat s reálnými daty na praktických příkladech a osvojíte si dovednosti v programování Pythonu, analýze vektorových a rastrových dat, webovém mapování i cloud computingu. Ať jste student, výzkumník, GIS profesionál nebo datový vědec, tato kniha vás vybaví nástroji pro sebevědomé řešení geoinformačních výzev.

  12. The Hundred-Page Guide to the Core Mathematics of Machine Learning
    The Hundred-Page Guide to the Core Mathematics of Machine Learning
    A Practical Introduction to Linear Algebra, Calculus, and Statistics with Python and NumPy
    PR

    Demystify the mathematical foundations of machine learning with this concise, hands-on guide. Dive into the essentials of linear algebra, calculus, and statistics, specifically tailored for practical application with Python and NumPy. No more wading through dense textbooks – get the core concepts you need to build intelligent systems, fast.

  13. The A-Z Beginner Python Guide
    The A-Z Beginner Python Guide
    Learn Python In 7 Days
    Kavyansh Mishra

    "Learn Python from scratch — no experience needed. From your very first line of code to building real projects, this guide takes you step-by-step through the A to Z of Python programming."

  14. Probabilistic Forecasting with Conformal Prediction in Python
    Probabilistic Forecasting with Conformal Prediction in Python
    The Practical Guide to Uncertainty Quantification for Data Science, Machine Learning, and Forecasting
    Valery Manokhin

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

  15. The Crystal Ball Instruction Manual, Volume Two
    No Description Available