Isbn: 9798291971567 - mastering dspy for agentic ai: optimize, automate, and scale your llm apps: 4 (intelligent agent systems: a developer's guide) (7 resultados)

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    Idioma: Inglés

    Editorial: Independently Published, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA

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    Editorial: Amazon Digital Services LLC - Kdp, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Editorial: Amazon Digital Services LLC - Kdp, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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

  • Idioma: Inglés

    Editorial: Independently published, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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  • Idioma: Inglés

    Editorial: Independently Published, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK

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  • Idioma: Inglés

    Editorial: Independently Published, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    EUR 23,84

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    Paperback. Condición: new. Paperback. Mastering DSPy for Agentic AI: Optimize, Automate, and Scale Your LLM AppsWhat if your AI agents could reason, adapt, and perform at scale-without endless trial and error, tangled code, or hidden bottlenecks? Today's developers, data scientists, and product teams want more than clever prototypes. They need robust, modular AI pipelines that can be inspected, optimized, and trusted to deliver results in production.Mastering DSPy for Agentic AI is the definitive guide for anyone building next-generation language model applications. This hands-on book reveals how DSPy, a cutting-edge agentic framework, empowers you to compose, manage, and monitor complex LLM-powered workflows with confidence and precision. Skip the headaches of brittle prompt chains and discover a toolkit engineered for real-world impact.Inside, you'll learn how to: Design agentic pipelines using DSPy's modular architectureImplement retrieval-augmented generation, ReAct, and Chain-of-Thought patternsIntegrate tools, databases, and APIs into seamless agent workflowsBenchmark and scale solutions using industry-standard practicesDebug, monitor, and refine agent behavior with MLflow and modern tracingAchieve reproducibility, robust error handling, and cost control from development to deploymentCurious how top teams move from concept to production AI-while keeping control over performance and costs? This book brings you proven strategies, code examples, and expert insights gathered from practical deployments and real-world use cases. Each chapter delivers actionable techniques, whether you're a software engineer, machine learning specialist, or technical leader aiming to deploy LLM apps with confidence.Don't let your AI projects stall in the prototype stage. Get the knowledge, clarity, and hands-on skills you need to architect resilient, scalable, and transparent agentic systems-ready for the demands of business, research, or the next breakthrough product. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Idioma: Inglés

    Editorial: Independently Published, 2025

    9798291971567

    Serie: Libro 4 de 5 - Intelligent Agent Systems: A Developer's Guide

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    EUR 25,21

    Envío por EUR 43,15 
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    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. Mastering DSPy for Agentic AI: Optimize, Automate, and Scale Your LLM AppsWhat if your AI agents could reason, adapt, and perform at scale-without endless trial and error, tangled code, or hidden bottlenecks? Today's developers, data scientists, and product teams want more than clever prototypes. They need robust, modular AI pipelines that can be inspected, optimized, and trusted to deliver results in production.Mastering DSPy for Agentic AI is the definitive guide for anyone building next-generation language model applications. This hands-on book reveals how DSPy, a cutting-edge agentic framework, empowers you to compose, manage, and monitor complex LLM-powered workflows with confidence and precision. Skip the headaches of brittle prompt chains and discover a toolkit engineered for real-world impact.Inside, you'll learn how to: Design agentic pipelines using DSPy's modular architectureImplement retrieval-augmented generation, ReAct, and Chain-of-Thought patternsIntegrate tools, databases, and APIs into seamless agent workflowsBenchmark and scale solutions using industry-standard practicesDebug, monitor, and refine agent behavior with MLflow and modern tracingAchieve reproducibility, robust error handling, and cost control from development to deploymentCurious how top teams move from concept to production AI-while keeping control over performance and costs? This book brings you proven strategies, code examples, and expert insights gathered from practical deployments and real-world use cases. Each chapter delivers actionable techniques, whether you're a software engineer, machine learning specialist, or technical leader aiming to deploy LLM apps with confidence.Don't let your AI projects stall in the prototype stage. Get the knowledge, clarity, and hands-on skills you need to architect resilient, scalable, and transparent agentic systems-ready for the demands of business, research, or the next breakthrough product. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.