Books

This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies. This book is based on the industry-leading Johns Hopkins Data Science Specialization.

SYSMOD is an MBSE toolbox for pragmatic modeling of systems. It is well-suited to be used with SysML. The book provides a set of methods with roles and outputs. Concrete guidances and examples show how to apply the methods with SysML.

“Happily purchased. Handy to have these in one place. Thank you!” — Kent Beck “Excellent new thinking on Domain-Driven Design. It's full of real practical experience in getting the most value from domain modelling. Just like the Eric Evans' DDD book, this gives more insight each time you read it.” — Ian Russell

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.

Explore the fascinating world of Artificial Intelligence and solve real-world problems! In this practical guide, you will build intelligent real-world applications using GPT-4, Embeddings, Whisper, Weaviate, and more tools from the OpenAI ecosystem. You don't need to be a data scientist or machine learning engineer to follow this guide!

Approaching PHP from a functional perspective. Yes, really. (With just a pinch of category theory.)

Grab your compiler and follow along as the authors develop and gradually refine a short Haskell program. This extremely approachable guide explains topics like case expressions, sum and product types, type constructors, typeclasses, and newtype coercion as they are motivated by the example code, with exercises to reinforce your understanding.

Preparation Guide for your TYPO3 CMS Certified Consultant exam.TYPO3 LTS 9+10 ready.

大規模言語モデル (LLM) の主要な概念から実践的な応用例まで、簡潔に図解されている学習ガイドです。プロジェクトでの利用、面接対策、個人的な学習にも最適です。

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 Yet many teams still rely on outdated or misleading measures like MAPE.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.

A collection of proven software engineering and architecture design method elements to accelerate project work and reduce technical risk. Suited for API design and (micro-)service architectures. Activity descriptions and artifact templates for non-functional requirements, domain models, architectural decision records, API contracts. Sample content.

A living digital book on artificial intelligence and human intelligence, exploring how AI is reshaping knowledge, creativity, innovation, uncertainty, and the human future.

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!

Design Patterns in Modern Perl shows all 23 classic “Gang of Four” patterns implemented in real, runnable modern Perl. See each pattern in bless/Class::Mite, Moo, and class/Object::Pad, with tests and benchmarks you can run yourself. Use it as a practical handbook for designing, refactoring, and modernising serious Perl applications.