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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Zustand: Neu. Neuware - Hermes AI Engineering: A Practical Guide to Building Autonomous AI Agents for Real-World Applications Have you ever built an AI agent that worked perfectly in a demo but failed when solving real-world problems Or struggled to connect language models, memory, tools, APIs, and workflows into a reliable system If you're ready to build AI agents that go beyond simple chatbots, this book is for you. Autonomous AI is transforming the way software is built. Modern AI agents can reason, plan, use tools, retrieve knowledge, and complete complex tasks with minimal human input. Building these systems, however, requires more than prompt engineering. It requires the right architecture, memory, orchestration, security, and deployment strategies. Hermes AI Engineering is a practical guide that teaches developers, AI engineers, software architects, and technology professionals how to build production-ready autonomous AI agents. Through clear explanations, real-world examples, and practical implementation techniques, you'll learn how to design intelligent systems that are reliable, scalable, and ready for real-world applications. Inside This Book, You'll Learn How To: - Build modern autonomous AI agents from the ground up.- Design systems for reasoning, planning, memory, and execution.- Integrate APIs, databases, external tools, and Retrieval-Augmented Generation (RAG).- Develop collaborative multi-agent systems and implement the Model Context Protocol (MCP).- Test, monitor, optimize, secure, and deploy AI applications for production.>Why This Book Is Different Rather than focusing on isolated AI techniques, this book takes a systems-first approach. You'll learn how every component works together to create intelligent agents that are reliable, maintainable, and capable of solving real business problems. Who Should Read This Book Perfect for software developers, AI engineers, machine learning practitioners, solution architects, automation engineers, computer science students, and anyone interested in building modern AI systems. Why You Shouldn't Wait Autonomous AI agents are rapidly becoming an essential part of modern software. Organizations everywhere are investing in intelligent automation, and professionals with these skills are in high demand. Learning these technologies now will help you stay ahead as AI continues to reshape the future of software development. Take the Next Step Stop building AI agents that only work in demonstrations. Learn how to create intelligent systems that reason, remember, use tools, and solve real-world problems with confidence. Get your copy of Hermes AI Engineering today and start building autonomous AI agents that are ready for production. …

Taschenbuch. Zustand: Neu. Neuware - Modeling Intelligence Systems: Build a Strong Mathematical Foundation for Artificial Intelligence, Machine Learning, Deep Learning, and Modern AI Applications Have you ever wondered what truly powers ChatGPT, autonomous vehicles, recommendation systems, facial recognition, or modern AI assistants Behind every intelligent system lies mathematics. If you've tried learning AI before and felt overwhelmed by complex equations or disconnected theory, you're not alone. The good news is that understanding the mathematics behind AI doesn't have to be intimidating-it simply requires the right guide. Modeling Intelligence Systems is a practical, beginner-friendly guide that explains the mathematical principles behind Artificial Intelligence, Machine Learning, and Deep Learning using clear language, intuitive explanations, and real-world examples. Rather than asking you to memorize formulas, this book helps you understand why they matter and how they are used to build intelligent systems. Whether you're a student, software developer, data scientist, AI enthusiast, or working professional, you'll develop the confidence to understand modern AI from the ground up. Inside this book, you'll learn the essential mathematics that powers today's AI systems, including linear algebra, calculus, probability, statistics, optimization, feature engineering, neural networks, deep learning, transformers, large language models, computer vision, reinforcement learning, recommendation systems, AI agents, model deployment, responsible AI, and the future of intelligent systems. Each topic is explained with practical examples, mathematical intuition, working code samples where appropriate, and exercises that reinforce your understanding. By the time you finish this book, you'll be able to read AI literature with greater confidence, understand how modern algorithms learn from data, make better technical decisions, and build a strong foundation for advanced topics in machine learning and artificial intelligence. Instead of relying solely on libraries and frameworks, you'll understand the mathematical ideas that make them work. Artificial intelligence is transforming software development, healthcare, finance, cybersecurity, education, manufacturing, robotics, and countless other industries. The professionals who understand both the theory and the practical application of AI will be best positioned to take advantage of these opportunities. Building that foundation today will prepare you for the technologies shaping tomorrow. If you're ready to move beyond using AI tools and start understanding the mathematics that powers them, scroll up and click 'Buy Now' to begin building a solid foundation in artificial intelligence today.…