Isbn: 9798268210224 - generative ai engineering with mlops: deploying, scaling, and monitoring llms and foundation models (9 resultados)

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  • Idioma: Inglés

    Editorial: Independently published, 2025

    9798268210224

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    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

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    Editorial: Independently Published, 2025

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  • Idioma: Inglés

    Editorial: Independently Published, 2025

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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

    9798268210224

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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  • Idioma: Inglés

    Editorial: Independently published, 2025

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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  • Idioma: Inglés

    Editorial: Independently Published, 2025

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

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    Paperback. Condición: new. Paperback. Deploying, Scaling, and Monitoring LLMs and Foundation Models to Build Production-Ready Chatbots, Agents, and Diffusion ModelsGenerative AI Engineering with MLOps is your complete, practical roadmap to deploying, scaling, and monitoring modern AI systems in real-world environments. Designed for engineers, data scientists, and forward-thinking leaders, this book bridges the gap between machine learning theory and practical MLOps execution-showing you how to move from prototype to production without compromise.Inside, you'll discover how to: Build reliable retrieval-augmented generation (RAG) systems that deliver grounded answersFine-tune large language models with LoRA/QLoRA for cost-efficient adaptationDeploy models at scale with vLLM, Ray Serve, Triton, and KServeDesign safe and efficient AI agents with tool orchestration, guardrails, and HITL strategiesOperationalize diffusion models with caching, quotas, and policy enforcementImplement observability, drift detection, and cost monitoring to ensure production stabilityEvery chapter includes hands-on labs with complete, working Python code explained step by step-so you don't just read about concepts, you build and run them. By the end, you'll have the skills and confidence to design and manage AI systems that are both powerful and trustworthy.Jacobs V. Bradley is a seasoned practitioner and educator in MLOps, Generative AI, and scalable cloud systems. With years of experience bridging research, engineering, and production deployment, Bradley brings a unique ability to simplify complex technologies without losing depth. His work emphasizes practical engineering, credibility, and time-tested workflows-ensuring readers gain actionable expertise that aligns with today's fast-moving AI landscape.Whether you're a professional upgrading your skills, a student stepping into AI engineering, or a business leader seeking to deploy cutting-edge systems, this book offers the clarity, practicality, and credibility you need to succeed.Unlock the tools of the next decade. Step into the world of Applied Generative AI Engineering and deliver AI solutions that truly work in production. 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

    9798268210224

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

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    EUR 21,97

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  • Idioma: Inglés

    Editorial: Independently Published, 2025

    9798268210224

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    EUR 24,88

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    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. Deploying, Scaling, and Monitoring LLMs and Foundation Models to Build Production-Ready Chatbots, Agents, and Diffusion ModelsGenerative AI Engineering with MLOps is your complete, practical roadmap to deploying, scaling, and monitoring modern AI systems in real-world environments. Designed for engineers, data scientists, and forward-thinking leaders, this book bridges the gap between machine learning theory and practical MLOps execution-showing you how to move from prototype to production without compromise.Inside, you'll discover how to: Build reliable retrieval-augmented generation (RAG) systems that deliver grounded answersFine-tune large language models with LoRA/QLoRA for cost-efficient adaptationDeploy models at scale with vLLM, Ray Serve, Triton, and KServeDesign safe and efficient AI agents with tool orchestration, guardrails, and HITL strategiesOperationalize diffusion models with caching, quotas, and policy enforcementImplement observability, drift detection, and cost monitoring to ensure production stabilityEvery chapter includes hands-on labs with complete, working Python code explained step by step-so you don't just read about concepts, you build and run them. By the end, you'll have the skills and confidence to design and manage AI systems that are both powerful and trustworthy.Jacobs V. Bradley is a seasoned practitioner and educator in MLOps, Generative AI, and scalable cloud systems. With years of experience bridging research, engineering, and production deployment, Bradley brings a unique ability to simplify complex technologies without losing depth. His work emphasizes practical engineering, credibility, and time-tested workflows-ensuring readers gain actionable expertise that aligns with today's fast-moving AI landscape.Whether you're a professional upgrading your skills, a student stepping into AI engineering, or a business leader seeking to deploy cutting-edge systems, this book offers the clarity, practicality, and credibility you need to succeed.Unlock the tools of the next decade. Step into the world of Applied Generative AI Engineering and deliver AI solutions that truly work in 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.…