Books

大多數企業能夠快速交付，但鮮少企業能夠大規模調適。《控制論企業》介紹了一個統一的營運模式，將人工智能、反饋迴路和平台思維植入您組織的基因中。了解如何建立一個能夠感知變化、持續學習，並將干擾轉化為策略優勢的系統。

Većina poduzeća može brzo isporučivati, ali rijetka se mogu prilagoditi u većem opsegu.Kibernetičko poduzeće predstavlja objedinjujući operativni model koji ugrađuje umjetnu inteligenciju, povratne veze i platformsko razmišljanje u DNK vaše organizacije. Saznajte kako izgraditi sustav koji osjeća promjene, kontinuirano uči i pretvara poremećaje u stratešku prednost.

Većina preduzeća može brzo isporučivati, ali rijetko koja se mogu prilagođavati u većem obimu.Kibernetsko preduzeće predstavlja objedinjujući operativni model koji ugrađuje vještačku inteligenciju, povratne sprege i platformsko razmišljanje u DNK vaše organizacije. Saznajte kako izgraditi sistem koji osjeća promjene, kontinuirano uči i pretvara poremećaje u stratešku prednost.

معظم المؤسسات قادرة على التنفيذ السريع، ولكن القليل منها يستطيع التكيف على نطاق واسع.يقدم كتاب المؤسسة السيبرانية نموذجاً تشغيلياً موحداً يدمج الذكاء الاصطناعي وحلقات التغذية الراجعة والتفكير المنصّي في الحمض النووي لمؤسستك. تعرف على كيفية بناء نظام يستشعر التغيير، ويتعلم باستمرار، ويحول الاضطرابات إلى ميزة استراتيجية.

La plupart des entreprises peuvent agir rapidement, mais peu peuvent s'adapter à grande échelle.L'Entreprise Cybernétique présente un modèle opérationnel unificateur qui intègre l'IA, les boucles de rétroaction et la pensée plateforme dans l'ADN de votre organisation. Découvrez comment construire un système qui détecte le changement, apprend en continu et transforme les perturbations en avantage stratégique.

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.

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!

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.

A model that wins on MAPE can lose money on the shelf. A 15% accuracy gain can hide a 12% bias. An interval that looks tight can be wrong a third of the time.Forecast metrics are decision instruments, not neutral truth detectors — and most teams are still choosing them by habit. This book shows where MAE, MAPE, sMAPE, WAPE, MASE, RMSSE, CRPS, pinball loss, energy scores, bias measures and cost-based metrics help, and where they quietly mislead.Twelve chapters take you from elicitation and baselines through intermittent demand, probabilistic and hierarchical scoring, and the accuracy–utility gap, to a production evaluation system with monitoring, drift detection, alerting and governance. Every metric arrives with its assumptions, every criticism carries a remedy, and a retrospective Walmart M5 case study runs throughout, with Python listings and reproducibility checks.For demand planners, forecasting data scientists, ML engineers and analytics leads who need evaluation choices they can defend. Measure what matters.

A model that wins on MAPE can lose money on the shelf. A 15% accuracy gain can hide a 12% bias. An interval that looks tight can be wrong a third of the time.Forecast metrics are decision instruments, not neutral truth detectors — and most teams are still choosing them by habit. This book shows where MAE, MAPE, sMAPE, WAPE, MASE, RMSSE, CRPS, pinball loss, energy scores, bias measures and cost-based metrics help, and where they quietly mislead.Twelve chapters take you from elicitation and baselines through intermittent demand, probabilistic and hierarchical scoring, and the accuracy–utility gap, to a production evaluation system with monitoring, drift detection, alerting and governance. Every metric arrives with its assumptions, every criticism carries a remedy, and a retrospective Walmart M5 case study runs throughout, with Python listings and reproducibility checks.For demand planners, forecasting data scientists, ML engineers and analytics leads who need evaluation choices they can defend. Measure what matters.

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.

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.

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.

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.