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Paperback. Zustand: new. Paperback. Master the Future of AI with Context Engineering - Transform Prompts into Production-Ready IntelligenceIn a world where AI is powering business, research, and innovation, simply knowing how to write prompts is no longer enough. Context engineering is the missing link that separates hobbyist experiments from scalable, production-ready AI systems. This book, "Context Engineering for AI: From Prompting to Production," gives you the complete blueprint to design reliable, cost-efficient, and high-performing LLM applications that thrive in real-world environments.Inside, you will learn how to structure context pipelines, implement Retrieval-Augmented Generation (RAG), optimize tokens for cost and speed, and add short-term and persistent memory for multi-turn conversations. Through hands-on projects, real-world case studies, and production-proven techniques, you'll gain the practical skills to transform AI from a concept into a business-ready solution.Written by Jacobs V. Bradley, a seasoned technology expert and thought leader in AI systems and intelligent automation, this book reflects up-to-date industry trends and provides actionable insights for developers, data scientists, AI engineers, and technology leaders. Whether you're building document intelligence for finance, customer support automation at scale, or multi-agent context routing systems, this guide empowers you to engineer AI solutions that are accurate, reliable, and future-proof.If you want to go beyond prompt engineering and gain the technical mastery that modern enterprises demand, this is the essential guide. Future-proof your skills, boost your AI expertise, and turn concepts into deployable, revenue-generating systems with context engineering.Perfect For: Developers and AI engineers building real-world LLM applicationsTech leaders seeking scalable, cost-efficient AI solutionsReaders of top-selling AI, machine learning, and automation books 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. 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.…
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Standard methods of chemical analysis. [V.1 The Elements; V.2 Industrial and natural products and noninstrumental methods; V.3 Instrumental methods]
Furman, N. Howell (Nathaniel Howell), 1892-1965 ; Welcher, Frank Johnson, 1907- ; Scott, Wilfred W. (Wilfred Welday) , 1876-1932 [Howard Bradley, W J Brown, O P Case, J R Churchill, P T Comisky, Leon Curtis, C Manning Davis, R G Ernst, Arnold Gahler, Morris Jacobs, Editha Karl-Kroupa, Herbert Marshall, R G Mercer, Edward G Moorehead, G H Morrison, M L Moss, J J Mulligan, A J Nicklay, George Oplinger, A R Powell, C J Rodden, S N Roeder, Chrales L Rulfs, Cecil Russell, Edward Scheffer, Stanislaus Skowronski, V A Stegner, John R Van Waser, Frank Vinci, G B Wengert, James R West, Roland S Young, C Zischkau, Raymon Pierson, Herbert Abraham, Walter Anderson, Gilbert Ayres, Ivan Jakovljevic, Peter Krumin, T S Ma, Max Tryon, Herbert Weisz]
Verlag: Princeton, N.J., Van Nostrand, 1966, 1966
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In den WarenkorbHardcover. Zustand: Fine. 5th or later Edition. 6th ed. ; 3 v. in 5. illus. (part col.) 24 cm. ; Contents: v. 1. The elements, N. H. Furman, editor.--v. 2. Industrial and natural products and noninstrumental methods, F. J. Welcher, editor. 2 v.--v. 3. Instrumental methods, F. J. Welcher, editor. 2 v. ; LCCN: 62-2869 ; LC: QD131; Dewey: 545 ; OCLC: 283405 ; black cloth ; ex-lib, stamps, labels, date dues, pockets ; Contents: Vol. 1 -- alkali metals aluminum antimony arsenic barium beryllium bismuth boron bromine cadmium calcium carbon cerium rare earth chlorine chromium cobalt copper flourine gallium germanium gold hydrogen indium iodine iron lead magnesium mercury moybdenum nickel vanadium titanium nitrogen oxygen phosphorus platinum radium rhenium technetium scandium selenium tellurium silicon silver strontium sulfur thallium thorium tin titanium tungsten uranium vanadium zinc zirconium hafnium -- Vol.2 Pt.1 Explosives propellants natural fats fertilizers fuel gases paper wood paint varnish lacquer pesticides petroleum plastics paint poisons rubber silicates soaps detergents soils vitamins water analysis -- Vol.2 Pt.2 Apparatus general operations and reagents -- Special techniques for industrial products and other special substances -- Vol.3 Pt.A Instrumental methods -- Instrumental methods for industrial products and other special substances -- Vol.3 Pt.B Instrumental methods in clinical medicine Natural fats Fertilizers Foods Organic functional groups Gases Glass Paint Paper Pesticide Petroleum Plastics Rubber Semiconductors Soaps Soils Water ; exhaustive; 5 thick heavy volumes ; the bible of chemical analysis, required reference in every laboratory ; FINE. Book.…

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Paperback. Zustand: new. Paperback. Master the Future of AI with Context Engineering - Transform Prompts into Production-Ready IntelligenceIn a world where AI is powering business, research, and innovation, simply knowing how to write prompts is no longer enough. Context engineering is the missing link that separates hobbyist experiments from scalable, production-ready AI systems. This book, "Context Engineering for AI: From Prompting to Production," gives you the complete blueprint to design reliable, cost-efficient, and high-performing LLM applications that thrive in real-world environments.Inside, you will learn how to structure context pipelines, implement Retrieval-Augmented Generation (RAG), optimize tokens for cost and speed, and add short-term and persistent memory for multi-turn conversations. Through hands-on projects, real-world case studies, and production-proven techniques, you'll gain the practical skills to transform AI from a concept into a business-ready solution.Written by Jacobs V. Bradley, a seasoned technology expert and thought leader in AI systems and intelligent automation, this book reflects up-to-date industry trends and provides actionable insights for developers, data scientists, AI engineers, and technology leaders. Whether you're building document intelligence for finance, customer support automation at scale, or multi-agent context routing systems, this guide empowers you to engineer AI solutions that are accurate, reliable, and future-proof.If you want to go beyond prompt engineering and gain the technical mastery that modern enterprises demand, this is the essential guide. Future-proof your skills, boost your AI expertise, and turn concepts into deployable, revenue-generating systems with context engineering.Perfect For: Developers and AI engineers building real-world LLM applicationsTech leaders seeking scalable, cost-efficient AI solutionsReaders of top-selling AI, machine learning, and automation books This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Paperback. Zustand: 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.…