Unlock the future of intelligent automation with Mastering Agentic AI, your comprehensive guide to designing, developing, and deploying autonomous AI agents that reason, adapt, and execute with unparalleled efficiency.
This practical engineering manual dives deep into Python-powered agentic workflows using LangGraph for stateful reasoning, RAG 2.0 for dynamic retrieval-augmented generation, and Modular Context Protocols (MCP) for seamless memory management. Whether you're crafting research assistants, compliance auditors, customer support bots, or enterprise-grade autonomous pipelines, this book equips you with executable code, architectural blueprints, and battle-tested best practices to transition from prototypes to production-ready intelligent systems.
Explore the core of agentic AI: from foundational LangGraph graphs for task orchestration and cyclic reasoning loops to advanced RAG 2.0 implementations featuring metadata filtering, hybrid semantic ranking, and traceable source attribution. Master secure tool integrations with Python automation scripts, robust error handling, retry mechanisms, and fallback strategies for real-world reliability.
Delve into multi-agent collaboration frameworks with role-based hierarchies, shared memory pools, message-passing protocols, and constitutional AI guardrails to ensure ethical, auditable outputs. You'll build scalable architectures incorporating MCP for context-aware user profiling, dynamic memory injection, and low-latency inference, all while embedding safety critics for bias detection and compliance enforcement.
This isn't abstract theory—it's a deployable toolkit loaded with complete Python codebases, FastAPI microservices, Docker containerization recipes, CI/CD automation pipelines, and real-time observability dashboards using Prometheus and Grafana. From single-agent prototypes to distributed multi-agent swarms, every chapter delivers step-by-step tutorials on optimizing performance, enhancing scalability, and mitigating risks in agentic ecosystems. Ideal for Python developers, AI engineers, data scientists, and DevOps specialists, Mastering Agentic AI transforms complex concepts into actionable intelligence.
Harness the power of autonomous agents to automate workflows, amplify decision-making, and drive innovation—your journey to agentic mastery begins now.
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Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. Unlock the future of intelligent automation with Mastering Agentic AI, your comprehensive guide to designing, developing, and deploying autonomous AI agents that reason, adapt, and execute with unparalleled efficiency. This practical engineering manual dives deep into Python-powered agentic workflows using LangGraph for stateful reasoning, RAG 2.0 for dynamic retrieval-augmented generation, and Modular Context Protocols (MCP) for seamless memory management. Whether you're crafting research assistants, compliance auditors, customer support bots, or enterprise-grade autonomous pipelines, this book equips you with executable code, architectural blueprints, and battle-tested best practices to transition from prototypes to production-ready intelligent systems. Explore the core of agentic AI: from foundational LangGraph graphs for task orchestration and cyclic reasoning loops to advanced RAG 2.0 implementations featuring metadata filtering, hybrid semantic ranking, and traceable source attribution. Master secure tool integrations with Python automation scripts, robust error handling, retry mechanisms, and fallback strategies for real-world reliability.Delve into multi-agent collaboration frameworks with role-based hierarchies, shared memory pools, message-passing protocols, and constitutional AI guardrails to ensure ethical, auditable outputs. You'll build scalable architectures incorporating MCP for context-aware user profiling, dynamic memory injection, and low-latency inference, all while embedding safety critics for bias detection and compliance enforcement. This isn't abstract theory-it's a deployable toolkit loaded with complete Python codebases, FastAPI microservices, Docker containerization recipes, CI/CD automation pipelines, and real-time observability dashboards using Prometheus and Grafana. From single-agent prototypes to distributed multi-agent swarms, every chapter delivers step-by-step tutorials on optimizing performance, enhancing scalability, and mitigating risks in agentic ecosystems. Ideal for Python developers, AI engineers, data scientists, and DevOps specialists, Mastering Agentic AI transforms complex concepts into actionable intelligence.Harness the power of autonomous agents to automate workflows, amplify decision-making, and drive innovation-your journey to agentic mastery begins now. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798268477955
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Vendeur : California Books, Miami, FL, Etats-Unis
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Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur LU-9798268477955
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. Unlock the future of intelligent automation with Mastering Agentic AI, your comprehensive guide to designing, developing, and deploying autonomous AI agents that reason, adapt, and execute with unparalleled efficiency. This practical engineering manual dives deep into Python-powered agentic workflows using LangGraph for stateful reasoning, RAG 2.0 for dynamic retrieval-augmented generation, and Modular Context Protocols (MCP) for seamless memory management. Whether you're crafting research assistants, compliance auditors, customer support bots, or enterprise-grade autonomous pipelines, this book equips you with executable code, architectural blueprints, and battle-tested best practices to transition from prototypes to production-ready intelligent systems. Explore the core of agentic AI: from foundational LangGraph graphs for task orchestration and cyclic reasoning loops to advanced RAG 2.0 implementations featuring metadata filtering, hybrid semantic ranking, and traceable source attribution. Master secure tool integrations with Python automation scripts, robust error handling, retry mechanisms, and fallback strategies for real-world reliability.Delve into multi-agent collaboration frameworks with role-based hierarchies, shared memory pools, message-passing protocols, and constitutional AI guardrails to ensure ethical, auditable outputs. You'll build scalable architectures incorporating MCP for context-aware user profiling, dynamic memory injection, and low-latency inference, all while embedding safety critics for bias detection and compliance enforcement. This isn't abstract theory-it's a deployable toolkit loaded with complete Python codebases, FastAPI microservices, Docker containerization recipes, CI/CD automation pipelines, and real-time observability dashboards using Prometheus and Grafana. From single-agent prototypes to distributed multi-agent swarms, every chapter delivers step-by-step tutorials on optimizing performance, enhancing scalability, and mitigating risks in agentic ecosystems. Ideal for Python developers, AI engineers, data scientists, and DevOps specialists, Mastering Agentic AI transforms complex concepts into actionable intelligence.Harness the power of autonomous agents to automate workflows, amplify decision-making, and drive innovation-your journey to agentic mastery begins now. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798268477955
Quantité disponible : 1 disponible(s)
Vendeur : Rarewaves.com UK, London, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur LU-9798268477955
Quantité disponible : Plus de 20 disponibles