Harold roop (24 Ergebnisse)
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Paperback. Zustand: new. Paperback. Mastering Slow AI: Using Critical Thinking to Make Smarter Decisions About Artificial Intelligence Every DayAre you relying on AI more than you should, but still wondering if you can trust the answers it gives? Many people use AI every day without knowing when to trust it, when to question it,… or when to think for themselves.Mastering Slow AI helps you use artificial intelligence with confidence and good judgment. Instead of blindly accepting AI-generated answers, you'll learn how to think critically, spot mistakes, verify information, and make smarter decisions at work, school, and in everyday life. The book explains when AI is the right tool, when it isn't, and how to combine AI with human thinking for better results. These themes are the foundation of the book's practical approach.Inside, you'll discover how AI works, where it falls short, how to avoid common mistakes, protect your privacy, prevent overdependence on AI, and build healthy habits that will remain valuable as technology continues to evolve. You'll also find step-by-step guidance, real-world examples, practical checklists, and easy-to-follow explanations that make even complex ideas simple to understand.Written using practical, tested principles, this book is designed for students, professionals, business owners, educators, and anyone who wants to use AI wisely instead of blindly.AI is changing the way we live and work every day. Don't wait until bad decisions become costly. Get your copy of Mastering Slow AI today and learn how to think first, verify wisely, and make better decisions with artificial intelligence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. Hermes Agent Development: Build Persistent AI Agents with Memory, Skills, MCP, Long-Running Workflows and Self-Improving Systems Have you spent hours trying to build a Hermes Agent, only to get stuck with confusing documentation, scattered tutorials, and AI agents that forget everything the mo…ment a session ends? If you've been piecing together information from blogs, videos, and online forums without getting the results you want, you're not alone.Many developers struggle to understand how to build AI agents that actually work in the real world. Setting up persistent memory can feel overwhelming. Connecting tools with MCP can be confusing. Creating reusable skills, managing long-running workflows, and building self-improving systems often require searching through outdated guides and incomplete examples. One small mistake can waste hours of debugging and leave you wondering what went wrong.Hermes Agent Development is the practical guide that makes everything clear. Written in simple, easy-to-follow language, this book takes you from the basics to building powerful, production-ready AI agents that can remember, learn, use tools, and complete complex tasks with confidence.Inside this book, you'll learn how to: - Install and configure Hermes Agent the right way- Build persistent AI agents with long-term memory- Create and manage reusable AI skills- Master the Model Context Protocol (MCP) for seamless tool integration- Connect AI agents to APIs, databases, cloud services, and external applications- Design long-running workflows that automate real-world tasks- Build self-improving AI systems that learn from feedback- Develop multi-agent systems that work together efficiently- Monitor, secure, optimize, and scale AI agents for production environments- Build practical AI projects you can use as the foundation for your own applicationsThis book is packed with step-by-step instructions, working code examples, clear illustrations, practical exercises, real-world projects, checklists, and best practices that help you avoid common mistakes and build reliable AI systems faster. Whether you're a software developer, AI engineer, Python programmer, student, or technology enthusiast, you'll gain the confidence to move beyond simple chatbots and start building intelligent AI agents that solve real business and engineering problems.The methods in this book are based on practical experience and proven development techniques, making it easier to understand not just what to do, but why it works. Instead of guessing your way through complex features, you'll have a clear roadmap that saves time and helps you build better AI applications from day one. AI agent development is evolving rapidly, and the developers who understand persistent memory, MCP, reusable skills, workflow automation, and self-improving systems will have a major advantage. Don't wait until you're left behind or spend countless hours trying to figure everything out on your own.Get your copy of Hermes Agent Development today and start building powerful, persistent AI agents with the knowledge, confidence, and practical skills to create intelligent systems that are ready for real-world use. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. Mastering AI Observability: A Practical Guide to Monitoring, Evaluating, Debugging and Optimizing Production AI SystemsHave you ever deployed an AI application that looked perfect in testing, only to fail, slow down, hallucinate, or become expensive once real users started using it? If you've…spent hours digging through logs, searching online for answers, or trying to figure out why your AI system isn't behaving the way it should, you're not alone.Modern AI systems are powerful, but they can also be difficult to understand. A small change in a prompt, model, dataset, or retrieval pipeline can lead to inaccurate answers, higher costs, poor performance, or frustrated users. Most documentation explains how to build AI applications, but very little shows you how to keep them running reliably in production.Mastering AI Observability was written to solve that problem. This practical guide shows you how to monitor, evaluate, debug, and optimize production AI systems with confidence. Whether you're working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, or modern machine learning applications, you'll learn how to understand what's happening inside your AI systems and fix problems before they affect your users.Inside this book, you'll learn how to: Build observable AI systems from the ground upCollect and analyze logs, metrics, traces, and telemetryMonitor LLMs, AI agents, and RAG applications in productionDetect hallucinations, model drift, latency issues, and performance bottlenecksUse OpenTelemetry, OpenInference, and modern observability toolsDebug AI failures and perform root cause analysisTrack token usage, infrastructure health, and operational costsImprove reliability, scalability, security, and user experienceYou'll also find step-by-step instructions, practical examples, real-world case studies, complete code samples, diagrams, dashboards, checklists, and best practices that make even complex observability concepts easy to understand and apply.Drawing on proven engineering practices and real production scenarios, the author explains each concept in clear, simple language that helps you move from theory to real-world implementation without feeling overwhelmed. Don't wait until hidden AI failures damage your application, increase your costs, or erode user trust. Learn how to monitor your AI systems the right way from the very beginning.Get your copy of Mastering AI Observability today and start building AI applications that are reliable, transparent, efficient and ready for production. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Zustand: new. Paperback. Mastering Domain-Specific LLMs: Build Production-Ready AI Models with Fine-Tuning, Knowledge Bases, Retrieval-Augmented Generation and LLMOps Tired of AI that sounds smart but gives the wrong answers when your work really matters?Many developers and AI teams start with a powerful large languag…e model, only to discover that it doesn't understand their business, industry, or private data. They spend hours reading scattered tutorials, trying different models, experimenting with fine-tuning, and building RAG pipelines that still return inaccurate or inconsistent results. Before long, valuable time is lost, costs go up, and production deployments become frustrating.If that sounds familiar, this book was written for you.Mastering Domain-Specific LLMs takes you step by step through the complete process of building AI systems that truly understand your organization's knowledge. Instead of focusing on theory alone, you'll learn practical methods that you can apply to real projects from day one.Inside this book, you'll learn how to: - Choose the right foundation model for your use case- Prepare high-quality datasets that improve AI performance- Fine-tune LLMs using modern techniques such as LoRA and QLoRA- Build knowledge bases that keep your AI accurate and up to date- Create Retrieval-Augmented Generation (RAG) pipelines that retrieve trusted information before generating answers- Work with embeddings, vector databases, and semantic search- Develop AI assistants that understand industry-specific documents and workflows- Deploy production-ready AI applications with APIs and cloud infrastructure- Monitor, evaluate, secure, and improve AI systems using modern LLMOps practices- Reduce hallucinations and build AI applications users can trustThis isn't a book filled with vague ideas or copied documentation. You'll find clear explanations, complete working code examples, practical projects, real-world use cases, hands-on exercises, architecture diagrams, implementation guidance, and proven engineering practices that help you avoid costly mistakes.Whether you're building AI for healthcare, finance, legal services, cybersecurity, education, manufacturing, customer support, or enterprise software, you'll gain the skills to create domain-specific AI systems that deliver reliable, accurate, and production-ready results.Written by an experienced AI practitioner, this book combines tested engineering methods with practical knowledge drawn from real-world AI development. Every chapter builds on the last, making even advanced topics easier to understand and apply. Don't waste weeks piecing together information from blog posts, videos, and outdated tutorials. Start building domain-specific LLMs the right way with a clear roadmap that takes you from the fundamentals to production deployment.Get your copy of Mastering Domain-Specific LLMs today and start building AI systems that understand your data, solve real business problems, and deliver results you can trust. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
