Books

800 pages. 11 chapters. The full forecasting stack in Python — from ARIMA to foundation models — with production-grade code and proper evaluation. No hype.

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.

Most people think they are bad at math. In reality, they were never taught arithmetic properly.This book is a modern English edition of Arithmetic by Alexander P. Kiselev—the text that formed the backbone of mathematical education in Russia and USSR for over a century and helped produce generations of exceptionally strong mathematicians, scientists, and engineers.Unlike modern textbooks that prioritise shortcuts, visuals, and lowered expectations, Kiselev builds arithmetic logically, systematically, and rigorously. Every method is explained. Every operation has meaning. Exercises are carefully sequenced to develop real understanding—not rote pattern-following.This book does not promise “easy math”. It promises something better: clarity, confidence, and competence.Whether you are a student, a parent, a tutor, or an adult rebuilding fundamentals, this book will change how you understand arithmetic—and why so much later mathematics suddenly becomes easier.

You’ll just need the Five Essential Elements of Learning Through five essential elements, you’ll gain the ability to learn anything deeply—no matter how complex the subject. These five pillars of effective learning will become lifelong tools, guiding you every time you set out to truly master new knowledge and retain it permanently. If you're ready to stop passively consuming information and start truly mastering it, this book is for you.

This third volume of the series on experiential learning concerns itself principally with creating those experiences that simulate some life situation. This volume focuses on those simulation exercises, providing lots of examples and variations, using all the senses and all parts of the brain.

Designed to demonstrate how to debrief educational experiences, Experiential Learning 2 : Invention is "a gold mine" of questions and exercises useful for conducting retrospectives of on-the-job work. What could be more eductational than on-the-job work?

Chinese Handwriting for Left-hander is a comprehensive guide that empowers left-handed individuals to write Chinese characters naturally, by overturning the right-handed assumptions embedded in traditional stroke orders, paper placement, and pen grip.

lego4scrum - eine der interaktivsten Methoden, um ein agiles Mindset und das Scrum Framework in Aktion zu demonstrieren. Dieses Buch fasst jahrelange Experimente und hunderte von lego4scrum-Workshops zusammen. Es wird Dir ermöglichen, Scrum auf eine völlig neue, frische und unterhaltsame Weise zu unterrichten. Dies ist die deutsche Ausgabe.

What do Atari games, schedule planning and self-piloted drones have in common? Find the answer in this book!

Um livro sobre como ser um cientista à maneira moderna e de código aberto.

What if wealth didn’t require self-betrayal? The INFJ Millionaire shows thoughtful, idealistic people how to build real financial freedom through calm strategy, ethical leverage, and systems that protect both their values and their energy.

A book about how to be a scientist the modern, open-source way.

A rigorous treatment of linear models for self learning data scientists. This book is only available in pdf form.