Computers and Programming

You know how to build classes in Protégé. But do you know when to attach meaning — and when to wait?Volume 4 of "Mastering Ontology Engineering" introduces SKDL: the Semantic Knowledge Development Lifecycle. Seven stages. One discipline. Zero guesswork.From Aristotle to Description Logic. From taxonomy to executable knowledge.This is where pizza -> philosophy — and philosophy -> engineering.

You tried AI tools. They're fast. And you're still doing all the work — just in a chat window.

Ready to move beyond the basics of Rust? This book takes you inside the language, from ownership and memory management to concurrency, networking and performance optimization. Build real systems projects, learn to track down tricky bugs and gain the skills to write Rust software that is fast, secure and reliable.

Stop memorizing SQL answers. Start solving real problems.Master 42 practical SQL challenges with tested queries, clear explanations, and hands-on exercises designed to build confidence for technical interviews.

A practical guide to numerical methods for the Cahn–Hilliard equation in alloy design—matrix and spectral schemes, quasi-steady reductions, and matrix exponentials—tested on spinodal benchmarks and illustrated with codes for binary and multicomponent systems.

A practical 30-day plan that turns complete beginners into confident, responsible users of AI coding assistants.Learn how to set clear goals, build a small project, debug with purpose, use Git, write better code, and present your work — all while using AI as a learning partner, not a crutch.

AI can speed up learning and coding — but only if you stay in control. This book shows new developers how to use GPT-6, Claude, and Cursor effectively: how to ask clear questions, supply useful context, review generated code, test edge cases, and avoid common mistakes such as invented APIs, insecure suggestions, and overconfident explanations. You will build practical habits for explanations, small features, tests, debugging, and documentation — while protecting private data and remaining responsible for the final result. Ideal for students, self-learners, and early-career developers who want to learn with AI, not instead of learning.

Stop getting stuck in manual regression cycles and learn to engineer zero-touch automation pipelines. In 30 days, go from Manual QA to SDET by building a production-grade test framework from scratch with Playwright, TypeScript, and GitHub Actions—complete with a live portfolio report for hiring managers.

Building a Native LLM Inference Engine Building a modern LLM inference engine from the ground up requires understanding every layer between model weights and generated tokens. This book provides a systems-level, implementation-focused path through that entire stack, from raw checkpoint formats and tensor memory layouts to native C++ execution, CUDA kernels, KV-cache management, scheduling, multi-GPU inference and production serving.

When systems fail, theory meets reality. This book explores how to design, build and operate software that holds up under pressure, from unexpected outages to subtle failures buried deep in the architecture. Learn the principles and practical techniques that help engineers make better decisions, reduce risk and build systems that keep working when things go wrong.

Arrays - Vol 3 (Intermediate → Advanced) - C++ Edition teaches 57 array algorithms through plain-language explanations, C++ implementations, and step-by-step visual walkthroughs, all in full color.

The code looks right. The agent sounds sure. Then it breaks. Learn the 50 most common ways AI-built apps fail, how to spot each one early, and how to fix it before your users find out.