Books

Transform the classic pizza.owl tutorial into a launchpad for cutting-edge semantic engineering! This hands-on guide bridges the gap between theory and practice, showing you exactly how to build ontology-based meta-models and deploy executable knowledge graphs. Master the "Diagramming as Code" methodologies of the Executable Knowledge Architecture (EKA) framework through a continuous, live-updated learning journey.

The definitive guide to agentic software engineering with Codex CLI, from prompting fundamentals to multi-agent orchestration, CI/CD integration, and enterprise deployment across 32 hands-on chapters.

Revised for PyTorch 2.x! In 2019, I published a PyTorch tutorial on Towards Data Science and I was amazed by the reaction from the readers! Their feedback motivated me to write this book to help beginners start their journey into Deep Learning and PyTorch. I hope you enjoy reading this book as much as I enjoy writing it.

Humanoid Robotics: From Design to DeploymentRobotics is no longer child’s play. The real breakthroughs don’t come from flashy demos or science fiction fantasies. They come from the hard, mathematical truths that govern how machines move, think, and interact with the world.

Master AI-powered infrastructure automation with this hands-on guide to building production-ready MCP servers and AI agents in Go. Transform from manual AWS operations to intelligent automation that understands your environment and makes smart decisions while keeping humans in control.

Learn how to implement various feature selection methods in a few lines of code and train faster, simpler, and more reliable machine learning models. Using Python open-source libraries, you will learn how to find the most predictive features from your data through filter, wrapper, embedded, and additional feature selection methods.

Usar IA para programar es fácil. Usarla sin perder el control, no tanto. Spec-Driven Development es el método para convertir tu idea en una spec que la IA ejecuta con precisión — sin loops infinitos, sin código roto, sin empezar de cero.

LLMs und Agentic AI sind derzeit Hype. Richtig angewendet können sie extreme positive Effekte bringen. Dieses Buch zeigt, vor welchen Herausforderungen man in großen Unternehmen und speziell auch in regulierten Umfeldern bei der Einführung stehen wird. Das Buch ist eine leicht lesbare Einführung für IT-nahe Führungskräfte und Enterprise Architekten und auch nützlich für IT-Profis allgemein, die in das Thema einsteigen möchten und absehbare Projektfehler vermeiden möchten

Using AI to code is easy. Using it without losing control — not so much.By week three, your project stops moving. The agent forgets decisions it made ten days ago. A change in auth breaks the dashboard. You spend more time re-explaining context than writing features. The code works, but only you know why — and you're not even sure you remember all of it.That's vibe coding hitting its ceiling.Spec-Driven Development is the method that replaces the chaos with a spec the AI actually executes. Not a ceremonial document. A working artifact: PRD, issues, tests, code — all traceable, all connected, all in the right order.This book shows you:How to grill your own idea before writing a single promptHow to write a PRD the AI won't misinterpretThe 7 phases that turn an idea into working softwareHow to use GitHub SpecKit and openSpec (and when not to)How to work this way in a team without slowing downThe 5 anti-patterns that destroy every spec22,000 words. 13 chapters. 5 appendices with ready-to-copy templates.No theory dumps. No filler. Just the method.

Vector stores don't think — they search. They find fragments that sound like your query, then forget they ever looked. Every session starts from nothing. Every context window is a memory that dissolves at sunset.But the deeper problem isn't amnesia. It's that when agents do remember, they remember in someone else's house — on servers you don't control, in formats you can't inspect, under terms you didn't write.Memory Graph is a book about building something different: persistent, structured, queryable memory that lives inside your application — no external servers, no data leaving your process, no infrastructure you don't own. An embedded graph database that travels with your agent the way a nervous system travels with a body.You'll learn how to model not just facts, but relationships between facts. Causality. Temporal ordering. The layered structure of meaning that makes memory more than a search index. You'll build ontologies that enforce what can be known and how. You'll combine graph traversal with semantic search — so your agents find not just what's similar, but what's connected.The result is an agent that remembers the way you do: structurally, contextually, privately — with memory that belongs to you.

Dive into the world of generative AI with "The ChatGPT Revolution" ebook. Understand the impact of ChatGPT, explore the vast potential of Large Language Models, and anticipate a multimodal AI-driven healthcare future. A must-read for those keen on the next medical revolution.

A practical guide to fine-tuning Large Language Models (LLMs), offering both a high-level overview and detailed instructions on how to train these models for specific tasks.Get the paperback version here. Get the Kindle version here.

"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

You don’t need massive compute or big-tech resources to build real AI. This hands-on guide shows you how to build and fine-tune your own small language model—from scratch—using accessible tools like Google Colab. Learn transformers step-by-step, train and align models on your own data, and deploy practical AI systems that run on consumer GPUs. If you’ve ever wondered “Can I build my own model?”—this book proves the answer is yes.

Este é um guia dinâmico, prático e visual para o novo e surpreendente mundo da IA Generativa. É como uma versão estendida do vídeo viral do Henrik com o mesmo nome. Versão impressa: Capa comum e Capa dura estão disponíveis na Amazon. Use o site da Amazon do seu país (ex: Amazon.se para a Suécia) para minimizar o tempo e custo de envio.