Books

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.

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.

The practical guide to AI-first teamwork. Includes access to the 'CollabAI AI companion' that helps you run your first session immediately. Most teams have fast individuals—but a slow system. AI can change that. CollabAI is the manual for teams who want to stop waiting and start flowing. It moves beyond "chatting with a bot" to a new collaborative rhythm where humans and AI build, test, and decide together in real time. Inside, you’ll discover:The Framework: How to run CollabAI sessions that compress weeks of work into hours.The Science: Why "System 2 Rituals" and psychological safety are the hard requirements for speed.The Scale: How to apply Joe Justice’s principles (Justice Boards & DSM) to run entire organizations without managers.The Future: How to transition safely to Agentic AI workflows using the Agion Pattern.Start optimizing the flow.

Your AI agent is only as smart as what it remembers. Most developers treat knowledge representation as an afterthought -- a data structure problem, not an architecture problem. They flatten complexity into schemas that can't express relationships, deploy embeddings without grounding, and build agents that degrade under their own reasoning load. This book changes that. **TypeDB for Edge AI Agents** is a practitioner's guide to building knowledge systems that actually work at the scale and complexity your agents demand. TypeDB is built on type theory -- the same mathematics that powers formal verification and programming language safety. For agents, that means you can express constraints that prevent bugs in your knowledge layer, reason about what's possible and what's forbidden, and build memory systems that don't require constant hallucination detection. With the Rust rewrite in TypeDB 3.0, your agents can carry sophisticated knowledge graphs on-device -- no round-trip to a server, no latency, no external dependencies. This book covers everything from the PERA data model and OWL ontologies to promise graphs for multi-agent coordination, giving you the patterns to design knowledge systems that scale without becoming incoherent. Whether you're an ML engineer, AI architect, or backend developer building production agent systems, this book bridges the gap between type theory and working code. You'll learn to design knowledge graphs that don't decay, structure agent memory that doesn't degrade over time, and coordinate multi-agent systems that respect causality and distributed constraints. Stop building agents that confidently hallucinate -- start building agents that reason correctly, remember reliably, and coordinate with certainty.

AI-Assisted Development verspricht Geschwindigkeit – aber Vibe Coding liefert oft Chaos. EXACT Coding zeigt, wie Software-Craft-Prinzipien und TDD als Korrektiv wirken: für Code, der schnell entsteht und trotzdem hält, was er verspricht.

Prompt engineering is dying. The future belongs to domain language engineers—developers who design structured DSLs that make AI reliable, deterministic, and scalable. This practical guide teaches you how to build the languages that shape AI-driven software. With templates, and real-world examples, you'll transform from AI user to AI architect. Stop negotiating with ChatGPT. Start engineering systems that work.

You already know how to build a Spring Boot service. Controllers, services, repositories, tests—it’s muscle memory. But what happens when your product manager asks for “an AI assistant” instead of “another REST endpoint”?Spring Boot Meets AI shows you how to plug modern AI models into the Spring applications you’re already running, using Spring AI’s fluent clients and Boot starters. You’ll go from zero to “curlable” AI endpoints in a few lines of code, then build up to real features: chat, summarisation, data extraction into POJOs, RAG over your own docs, and AI workflows that can safely call your own Java code.No new language. No separate AI microservice nobody wants to maintain. Just Spring Boot, Spring AI, and a set of patterns you can take back to work on Monday

What You Will Master: The Enterprise Stack: Google Gemini + Wolfram + Watson. The Open Source Stack: Llama 3 + SymPy + ChromaDB (fully offline). The Outcome: Self-healing, near-infallible agents that never lie about data

A practical guide to AI agent security for enterprise teams. Learn how to secure AI agents in production with bounded autonomy, AgentSecOps, MCP security, RAG governance, identity controls, audit evidence, and regulatory readiness.

Most enterprises can deliver fast, but few can adapt at scale.The Cybernetic Enterprise introduces a unifying operating model that embeds AI, feedback loops, and platform thinking into the DNA of your organization. Learn how to build a system that senses change, learns continuously, and transforms disruption into strategic advantage.

AI can generate code faster than ever. But speed is no longer the hardest part of software development.The real challenge is building systems where generated code remains correct, controlled, and aligned with architectural intent. Becoming a Harness-Driven Developer introduces a new development model for the age of AI-assisted engineering - one where developers focus less on writing every line by hand and more on defining the rules, structure, and enforcement mechanisms within which AI code agents operate.Through a practical repository mapped directly to the book’s chapters, this book shows how to move from ad hoc coding to a harness-driven approach based on specification, architecture, invariants, controlled execution, and system evolution. This is a book about staying in control while software development changes.

Claude Code é a ferramenta mais poderosa que a maioria dos desenvolvedores usa a 10% do potencial. Em 18 capítulos práticos, você vai construir uma aplicação full-stack do zero enquanto domina hooks, subagentes, servidores MCP, skills customizadas e tudo que separa quem digita prompts de quem orquestra agentes de IA.  

The definitive guide to Cursor, the AI-native IDE used by half the Fortune 500. From tab completion to Agent Mode, from .cursorrules to Composer — 14 chapters covering everything developers need to master the IDE that thinks with you.

Become a better data scientist by understanding different modeling mindsets.

A hands-on guide to downloading, running, serving, and maintaining open-weight LLMs on your own machine (489 manuscript pages).