Books

Linux is one of the best decisions you can make for your computer — but knowing where to start is the hard part. This guide walks you through everything: choosing a distribution, installing it, and using it confidently every day. It was written by Jay LaCroix of Learn Linux TV, for complete beginners. No prior experience required.

"If you intend to use machine learning to solve business problems at scale, I'm delighted you got your hands on this book." —Cassie Kozyrkov, Chief Decision Scientist at Google "Foundational work about the reality of building machine learning models in production." —Karolis Urbonas, Head of Machine Learning and Science at Amazon

The modeling of variants is a common use case in MBSE (for example for product line engineering or trade-off studies). Although SysML does not provide explicit model elements for variants, it is possible to create a variant model with SysML. The book explains the approach and provides a SysML profile for variants. 

Hands on Labs to prepare you for a career in Linux or system engineering. Built by the Professional Linux User's Group to focus on exactly what the professional needs in the enterprise.

Application sandboxing is the foundation of secure modern computing. This book explores the principles, architectures, and technologies behind containers, virtual machines, browser sandboxes, WebAssembly, and more, explaining how they isolate untrusted code, where their security boundaries break down, and how to choose the right approach for real-world systems.

A pattern language for event sourced applications and reliable distributed systems. Examples are written in the Python programming language. Now includes event-oriented introductions to the pattern language scheme of Christopher Alexander, the process philosophy of Alfred North Whitehead, and the person-centred psychology of Rogers and Rosenberg.

"The authors combine the views of their disciplines and look at larger issues such as the interplay between systems and people, the abstract and concrete, and the theoretical and practical . The authors' style is light and sometimes humorous with a large number of quotations from literature. . . . Never dull . . . the book bears evidence of a global view in which systems design is a means if organizing ideas, structures, things, and experience."

One of the wonderful things about the Weinbergs' series of books -- and this one in particular -- is that the ideas and the examples really make you think. With examples chosen from many fields, the book illustrates its central ideas with a cross-fertilization that helps one think outside ones box.

A true classic, not just in computing but in the broad area of scholarship. It is partly about the philosophy and mechanisms of science; partly about designing things so they work but mostly it is about how humans view the world and create things that match that view. This book will still be worth reading for a long time to come. - Charles Ashbacher

This book familiarizes readers with the world of LLM and agentic AI, and helps them quickly gain a working-level knowledge of building useful agentic AI solutions for process industry operations. With no prerequisites required, practical demo applications, and a hands-on approach adopted throughout, this book makes advanced AI technologies accessible to process engineers and data scientists alike. It aims to help process data scientists and engineers take their first confident steps into Agentic AI world, understand the full picture, and build a strong enough foundation to keep learning and building on their own. Also available here.

This short book introduces process data scientists to knowledge graphs and GraphRAG, a powerful combination that overcomes the limitations of vanilla RAG when answering the kind of cross-document, relationship-heavy questions that process engineers usually care about. With a hands-on, application-driven approach, the book walks readers through the complete pipeline: designing an ontology for plant data, using LLMs to extract entities and relationships from incident reports, building and querying the graph in Neo4j, and finally assembling everything into a demo web application.

The best way to thoroughly consider stakeholders and their values when designing something big and complex.

This book is a quick foray into the world of deep learning-based computer vision and abnormal equipment sound detection. The readers are introduced to the ease with which powerful equipment and product quality monitoring solutions can be built using sound and visual data.

The biggest challenge in implementing Standard Work is finding the right balance: Between giving employees clear, repeatable standards — and giving them space to think, improve, and grow.

Inference engineering is now its own discipline, with unique challenges around speed, cost, reliability and scale. This practical guide takes you from core concepts to production systems, showing how modern inference architectures work, how to optimize them and how to make better engineering decisions through measurement and trade-off analysis.