Ethan quan (27 Ergebnisse)
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Paperback. Zustand: new. Paperback. Master the art of building scalable and reliable autonomous systems with Developing Agentic AI: Patterns and Architectures for Autonomous Systems, a definitive guide tailored for AI engineers. Authored by Ethan Quan, this 14-chapter book explores cutting-edge workflow patterns and architecture…s, diving into goal decomposition, ReAct reasoning, and reflection loops to create intelligent agentic systems. Learn to implement tool chaining, orchestrate multi-agent collaborations, and manage short-term and long-term memory layers with practical code snippets in Python and TypeScript.The book addresses scalability strategies like rate limiting and sandbox execution, self-healing deployments, and monitoring for drift with performance optimization techniques. Discover governance models for responsible AI, cost optimization in agentic workflows, and the power of low-code agent factories for rapid development. Enriched with real-world case studies-such as scaling DevOps and customer support agents-this guide bridges the gap from ad-hoc scripts to robust, production-ready solutions. Ideal for AI engineers seeking to design resilient, maintainable agentic systems, this book requires no advanced prerequisites-just a drive to innovate. With concise tutorials and actionable checklists, achieve impactful results quickly.Key Topics: Agentic systems, workflow patterns, goal decomposition, ReAct reasoning, reflection loops, tool chaining, multi-agent collaboration, memory management, scalability, rate limiting, self-healing deployments, drift monitoring, governance, cost optimization, low-code development, real-world case studies.Who This Book Is For: AI Engineers designing autonomous workflows.Developers building scalable agentic architectures.Data Scientists optimizing multi-agent systems.Product Leaders overseeing AI system reliability.No prior agentic system expertise needed-just a passion for AI innovation.Why Choose This Book?Comprehensive Approach: From workflow patterns to production-ready systems.Practical Insights: Hands-on tutorials and code for immediate application.Future-Focused: Explores emerging trends in agentic system design.Ready to develop scalable, reliable agentic AI? Get Developing Agentic AI: Patterns and Architectures for Autonomous Systems today and revolutionize your AI engineering projects This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Zustand: new. Paperback. Unlock the power of transformer large language models (LLMs) with Crafting Intelligent AI Agents: Leveraging Transformer LLMs for Real-World Applications, a comprehensive, hands-on guide designed for developers, AI engineers, data scientists, and product leaders eager to build production-ready… AI agents. Authored by Ethan Quan, this 14-chapter book dives deep into transformer fundamentals, covering attention mechanisms, embeddings, and architectures, and progresses to advanced topics like pretraining, fine-tuning at scale, and retrieval-augmented generation. Master self-correcting planning loops, tool integration, and robust inference pipelines with step-by-step tutorials, practical code snippets in Python and TypeScript, and real-world case studies such as boosting agent reliability by 25% with optimized prompting.Explore scalability and resilience in deployment, monitoring and governance for ethical AI, cost optimization strategies, and security best practices for transformer models. The book culminates in a detailed guide to deploying autonomous agents to production, enriched with insights from real-world transformer applications and a forward-looking chapter on future trends. Whether you're a beginner with no prior transformer expertise or an enthusiast seeking to enhance decision-making and workflow automation, this book equips you with the tools to create intelligent, scalable, and secure AI agents. With concise lessons and actionable checklists, achieve tangible results in days, not months, and transform your AI ambitions into reality.Key Topics: Transformer LLMs, attention mechanisms, pretraining, fine-tuning, retrieval-augmented generation, self-correcting planning loops, tool integration, inference pipelines, scalability, resilience, monitoring, governance, cost optimization, security, production deployment, ethical AI, real-world case studies.Who This Book Is For: Developers integrating AI into applications.AI Engineers building autonomous systems.Data Scientists automating analyses with transformers.Product Leaders defining AI roadmaps.No prior transformer knowledge required-just curiosity and drive.Why Choose This Book?Comprehensive Coverage: From transformer internals to production deployment.Practical Focus: Hands-on tutorials and reusable code for immediate impact.Future-Ready: Insights into emerging trends in transformer-based AI agents.Ready to craft intelligent, production-ready AI agents? Get Crafting Intelligent AI Agents: Leveraging Transformer LLMs for Real-World Applications today and start building transformative solutions! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Sprache: Englisch
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Paperback. Zustand: new. Paperback. Elevate your AI agents with Empowering AI Agents with Context: Data Integration for Intelligent Decision Making, a comprehensive guide for developers seeking to enhance AI with real-time data. Authored by Ethan Quan, this 14-chapter book explores context-aware data integration, starting with d…evelopment environment setup and bootstrapping MCP server projects. Master integration with tools like GitHub, Slack, and Google Drive, and learn secure access and authentication best practices, rate limiting, caching, and logging for efficient operations.Delve into deploying context-aware agents on cloud platforms, building robust data pipelines for real-time access, and ensuring security and compliance in data-integrated AI systems. With practical code examples in Python and TypeScript, the book offers scalability insights for large-scale data integration and real-world case studies, such as streamlining code management and collaborative workflows. Ideal for developers aiming to build high-performance, secure AI agents, this book requires no advanced prerequisitesnjust a desire to innovate. Featuring concise tutorials and actionable checklists, achieve transformative results quickly.Key Topics: Context-aware AI, data integration, MCP servers, real-time data access, GitHub/Slack/Google Drive integration, secure authentication, rate limiting, caching, logging, cloud deployment, data pipelines, security compliance, scalability, code management, collaborative workflows, real-world case studies.Who This Book Is For: Developers integrating real-time data into AI systems.AI Engineers enhancing agent performance with context.Data Scientists optimizing decision-making processes.Product Leaders leveraging data-driven AI strategies.No prior context-aware expertise needed-just a drive to excel.Why Choose This Book?Comprehensive Guide: From setup to scalable deployment.Practical Tools: Hands-on tutorials and code for instant impact.Forward-Looking: Highlights future trends in context-aware AI.Ready to empower your AI agents with context? Get Empowering AI Agents with Context: Data Integration for Intelligent Decision Making today and unlock intelligent, data-driven solutions! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Sprache: Englisch
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Paperback. Zustand: new. Paperback. Unlock the power of transformer large language models (LLMs) with Crafting Intelligent AI Agents: Leveraging Transformer LLMs for Real-World Applications, a comprehensive, hands-on guide designed for developers, AI engineers, data scientists, and product leaders eager to build production-ready… AI agents. Authored by Ethan Quan, this 14-chapter book dives deep into transformer fundamentals, covering attention mechanisms, embeddings, and architectures, and progresses to advanced topics like pretraining, fine-tuning at scale, and retrieval-augmented generation. Master self-correcting planning loops, tool integration, and robust inference pipelines with step-by-step tutorials, practical code snippets in Python and TypeScript, and real-world case studies such as boosting agent reliability by 25% with optimized prompting.Explore scalability and resilience in deployment, monitoring and governance for ethical AI, cost optimization strategies, and security best practices for transformer models. The book culminates in a detailed guide to deploying autonomous agents to production, enriched with insights from real-world transformer applications and a forward-looking chapter on future trends. Whether you're a beginner with no prior transformer expertise or an enthusiast seeking to enhance decision-making and workflow automation, this book equips you with the tools to create intelligent, scalable, and secure AI agents. With concise lessons and actionable checklists, achieve tangible results in days, not months, and transform your AI ambitions into reality.Key Topics: Transformer LLMs, attention mechanisms, pretraining, fine-tuning, retrieval-augmented generation, self-correcting planning loops, tool integration, inference pipelines, scalability, resilience, monitoring, governance, cost optimization, security, production deployment, ethical AI, real-world case studies.Who This Book Is For: Developers integrating AI into applications.AI Engineers building autonomous systems.Data Scientists automating analyses with transformers.Product Leaders defining AI roadmaps.No prior transformer knowledge required-just curiosity and drive.Why Choose This Book?Comprehensive Coverage: From transformer internals to production deployment.Practical Focus: Hands-on tutorials and reusable code for immediate impact.Future-Ready: Insights into emerging trends in transformer-based AI agents.Ready to craft intelligent, production-ready AI agents? Get Crafting Intelligent AI Agents: Leveraging Transformer LLMs for Real-World Applications today and start building transformative solutions! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Sprache: Englisch
Verlag: Independently Published, 2025
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Paperback. Zustand: new. Paperback. Elevate your AI agents with Empowering AI Agents with Context: Data Integration for Intelligent Decision Making, a comprehensive guide for developers seeking to enhance AI with real-time data. Authored by Ethan Quan, this 14-chapter book explores context-aware data integration, starting with d…evelopment environment setup and bootstrapping MCP server projects. Master integration with tools like GitHub, Slack, and Google Drive, and learn secure access and authentication best practices, rate limiting, caching, and logging for efficient operations.Delve into deploying context-aware agents on cloud platforms, building robust data pipelines for real-time access, and ensuring security and compliance in data-integrated AI systems. With practical code examples in Python and TypeScript, the book offers scalability insights for large-scale data integration and real-world case studies, such as streamlining code management and collaborative workflows. Ideal for developers aiming to build high-performance, secure AI agents, this book requires no advanced prerequisitesnjust a desire to innovate. Featuring concise tutorials and actionable checklists, achieve transformative results quickly.Key Topics: Context-aware AI, data integration, MCP servers, real-time data access, GitHub/Slack/Google Drive integration, secure authentication, rate limiting, caching, logging, cloud deployment, data pipelines, security compliance, scalability, code management, collaborative workflows, real-world case studies.Who This Book Is For: Developers integrating real-time data into AI systems.AI Engineers enhancing agent performance with context.Data Scientists optimizing decision-making processes.Product Leaders leveraging data-driven AI strategies.No prior context-aware expertise needed-just a drive to excel.Why Choose This Book?Comprehensive Guide: From setup to scalable deployment.Practical Tools: Hands-on tutorials and code for instant impact.Forward-Looking: Highlights future trends in context-aware AI.Ready to empower your AI agents with context? Get Empowering AI Agents with Context: Data Integration for Intelligent Decision Making today and unlock intelligent, data-driven solutions! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Sprache: Englisch
Verlag: Independently Published, 2025
- Softcover
- Print-on-Demand
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Paperback. Zustand: new. Paperback. Master the art of building scalable and reliable autonomous systems with Developing Agentic AI: Patterns and Architectures for Autonomous Systems, a definitive guide tailored for AI engineers. Authored by Ethan Quan, this 14-chapter book explores cutting-edge workflow patterns and architecture…s, diving into goal decomposition, ReAct reasoning, and reflection loops to create intelligent agentic systems. Learn to implement tool chaining, orchestrate multi-agent collaborations, and manage short-term and long-term memory layers with practical code snippets in Python and TypeScript.The book addresses scalability strategies like rate limiting and sandbox execution, self-healing deployments, and monitoring for drift with performance optimization techniques. Discover governance models for responsible AI, cost optimization in agentic workflows, and the power of low-code agent factories for rapid development. Enriched with real-world case studies-such as scaling DevOps and customer support agents-this guide bridges the gap from ad-hoc scripts to robust, production-ready solutions. Ideal for AI engineers seeking to design resilient, maintainable agentic systems, this book requires no advanced prerequisites-just a drive to innovate. With concise tutorials and actionable checklists, achieve impactful results quickly.Key Topics: Agentic systems, workflow patterns, goal decomposition, ReAct reasoning, reflection loops, tool chaining, multi-agent collaboration, memory management, scalability, rate limiting, self-healing deployments, drift monitoring, governance, cost optimization, low-code development, real-world case studies.Who This Book Is For: AI Engineers designing autonomous workflows.Developers building scalable agentic architectures.Data Scientists optimizing multi-agent systems.Product Leaders overseeing AI system reliability.No prior agentic system expertise needed-just a passion for AI innovation.Why Choose This Book?Comprehensive Approach: From workflow patterns to production-ready systems.Practical Insights: Hands-on tutorials and code for immediate application.Future-Focused: Explores emerging trends in agentic system design.Ready to develop scalable, reliable agentic AI? Get Developing Agentic AI: Patterns and Architectures for Autonomous Systems today and revolutionize your AI engineering projects This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
