Books

안드로이드 기술 면접에서 좋은 결과를 얻으려면 단순히 답을 외우는 것이 아니라, 개념을 올바르게 이해하고 실전에 적용해 보는 연습이 중요합니다. 이 책에서 다루는 108개의 면접 질문, 162개의 추가적인 실전 질문, 50개 이상의 Pro Tips를 통해 기술적 배경과 논리를 향상시킴으로써 실제 기술 면접의 대비뿐만 아니라, 안드로이드 생태계의 전반적인 지식을 학습하는데 큰 도움이 됩니다. 하드커버 에디션 (영문) | 페이퍼백 에디션 (영문) ISBN: 979-8285926436

Event-Driven Architecture with Spring Boot 4.x and Kafka 4.x is a hands-on, code-first guide to building resilient, scalable systems with real-world patterns like CQRS, event sourcing, sagas, outbox, idempotency, schema evolution, observability, and testing. Each chapter focuses on one concept and backs it with practical trade-offs, failure modes, and runnable Spring Boot projects you can clone and run today. If you want to move beyond buzzwords and actually ship event-driven systems that hold up in production, this book is for you.

For the first time ever, C++23 changes "Hello World" in C++. What kind of fundamental changes does this mean for your code?

본 책은 단순히 “코틀린을 어떻게 사용하는가”를 넘어, “코틀린이 실제로 어떻게 동작하는가”까지 안내합니다. 내부 구현을 들여다보고, 바이트코드와 컴파일러의 동작을 명확히 탐구하며, 언어를 형성하는 핵심 내부 구조를 파헤칩니다. 기초 문법부터 코루틴, 컴파일러에 이르기까지 더 깊이 이해하고, 더 자신 있게 코틀린 코드를 작성하고 싶은 분들께는 좋은 지침서가 될 것입니다. 특히, 우리가 일상에서 친숙하게 사용하던 모든 언어적인 형태가 왜 지금과 같은 형태로 설계되었는지를 탐구하며 사고의 깊이를 더할 수 있습니다. Hardcover | Paperback | ISBN: 979-8243872744 [Course] Practical Kotlin Deep Dive Course

Troubleshooting Linux systems can feel like solving a mystery—but the right strategies make all the difference. This ebook teaches practical techniques, tools, and real-world approaches that help you diagnose problems faster and fix them with confidence.

Build a complete LLM inference engine in C++ — from a blank project to a working Transformer that loads a real model and generates text. Forged one challenge at a time, with tests that prove every piece works before you move on.

Metagraphs for Agentic AI: Beyond Triples, Beyond HypergraphsFrom Knowledge Graphs to Knowledge ArchitecturesThe triple is not enough.Every AI engineer building agent memory hits the same wall. You model a meeting as a knowledge graph triple — and immediately lose the fact that five people were in the room, a decision was made, and that decision caused three downstream actions. You reify. You flatten. You create workarounds. And your "knowledge graph" becomes a tangle of auxiliary nodes that machines can traverse but no human can reason about.This book shows you the way out. What You'll Learn Metagraphs are graph structures where edges connect sets of nodes to sets of nodes — and where edges themselves can be referenced as first-class nodes. They are the missing data structure for AI agents that need to remember, reason, and coordinate like humans do.This book takes you on a complete journey:Hypergraphs first. You'll learn what they are, why they matter, and where they break down. You'll implement them three ways — in SQL, in LadybugDB (Cypher), and in TypeDB — so you understand the tradeoffs viscerally, not just theoretically.Then metagraphs. You'll see how metagraphs solve the fundamental hypergraph problem (edges that can't be nodes), explore RDF named graphs as a lightweight metagraph, and implement full metagraphs in the same three database paradigms with production-ready, commented code.Then the big ideas. Semantic Spacetime. Holonic systems. Human cognitive architecture mapped to graph structures. Multi-agent coordination. Promise Theory for autonomous AI networks. This is where metagraphs stop being a data structure and become an architecture for intelligence. Who This Book Is For You're a software engineer, AI researcher, or knowledge graph practitioner who builds real systems. You've used Neo4j or RDF stores. You've built RAG pipelines. You've felt the limits. You want to know what comes next.No PhD required. Every concept comes with working code in SQL, Cypher, TypeQL, SPARQL, and Python. What Makes This Book Different This isn't a theoretical monograph. It's the distillation of two and a half years of research, 130+ published articles, and hands-on implementation at the intersection of knowledge graphs and agentic AI.Every chapter bridges theory and practice. You'll read about Basu and Blanning's formal metagraph definition — and then build the schema in PostgreSQL. You'll learn Mark Burgess's Promise Theory — and then model a multi-agent coordination protocol as a six-layer promise graph. You'll understand why labeled property graphs are secretly metagraphs — and what that means for your Neo4j deployment today. 18 Chapters. Three Parts. One Argument. Part I — The Hypergraph Foundation (7 chapters): From the knowledge representation crisis through hypergraph theory to three complete database implementations.Part II — The Metagraph Solution (5 chapters): Metagraphs as the answer, RDF named graphs as a bridge, and three full metagraph implementations with detailed commentary.Part III — Theory Meets Practice (6 chapters): Semantic Spacetime, labeled property graphs, AI memory and human cognition, holonic systems, agent-to-agent interaction, and Promise Graphs for network-of-networks coordination. The Core Thesis If you want AI agents that reason like humans, you need knowledge structures that capture how humans actually organize knowledge — not as flat collections of facts, but as nested, hierarchical, context-rich, temporally-aware structures where relationships themselves carry meaning and can be the subject of further reasoning.Metagraphs are that structure. This book shows you why, and how to build with them.

If you are able to contribute, it will go to support OpenIntro (not the author), a US-based nonprofit working to spread open materials, e.g. by providing desk copies to instructors considering this text. This listing is in collaboration with the textbook's author, Jim Hefferon. Linear Algebra's official websitePaperbacks are $22openintro.org

All new language and library features of C++17 (for those who know previous versions). Learn how C++17 impacts day-to-day C++ programming, how to benefit in practice, how to combine new features, and how to avoid all new traps.Hardcover version (please, prefer a local bookstore) Paperback versionSpanish versionC++23C++20Bundle with C++ Move Semantics

#1 Best Seller in Management Science (Amazon International, France, Germany, Netherlands, Poland, Sweden – Feb 2026) and in other categories. Available worldwide on Amazon (Hardcover, Paperback, Kindle) and across all major digital platforms, including Leanpub, Apple Books, and Google Play. Learn how to drive your organizational performance with people and AI to 10X and beyond — in impact and relevance.

This series of test-driven small coding puzzles lets you code a database from scratch (no dependencies).We'll cover KV storage engines, LSM-Tree indexes, SQL, concurrent transactions, ACID, etc.

A practical guide to product engineering in an AI native era, where building shifts from manual construction to steering tools, editors, and agents. Product Engineering with AI covers platforms, agentic workflows, prompting, code quality, UX, and responsible practices for getting from prototype to production. 

IT Freelancing 2.0 zeigt dir, wie du dich als IT-Freelancer vom austauschbaren Projektarbeiter zum gefragten Experten entwickelst. Statt ständig um den nächsten Vertrag zu kämpfen, lernst du, dich klar zu positionieren, ergebnisorientierte Angebote zu gestalten und dir ein Geschäft mit echtem Zukunftswert aufzubauen.

A master class on the fundamentals and principles of functional programming. It contains 20 programming challenges with detailed solutions and 44 quizzes with answers and explanations. Moreover, 84 diagrams graphically illustrate how concepts and techniques work. Two real-world use cases show how to apply functional programming in practice.

Actionable Agile Metrics for Predictability is a comprehensive guide on how to use flow metrics and analytics to get the predictability your customers crave.