large language models enterprise (35 resultados)

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Paperback. Condición: New. Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions.By leveraging Big Data engineering and popular data cataloguing tools, you'll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. You'll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking.This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business.What You Will LearnExamine the various phases of an AI Enterprise Applications implementation.Turn from AI engineer or Data Science to an Intelligent Enterprise Architect.Explore the seamless integration of AI in Big Data Pipelines.Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle.Plan and implement end-to-end large-scale enterprise AI applications with confidence.Who This Book Is ForEnterprise Architects, Technical Architects, Project Managers and Senior Developers.

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Paperback. Condición: New. Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions.By leveraging Big Data engineering and popular data cataloguing tools, you'll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. You'll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking.This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business.What You Will LearnExamine the various phases of an AI Enterprise Applications implementation.Turn from AI engineer or Data Science to an Intelligent Enterprise Architect.Explore the seamless integration of AI in Big Data Pipelines.Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle.Plan and implement end-to-end large-scale enterprise AI applications with confidence.Who This Book Is ForEnterprise Architects, Technical Architects, Project Managers and Senior Developers.

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Taschenbuch. Condición: Neu. Prompt Engineering in the Enterprise - An Introduction | Competitive Advantages through Generative AI and Large Language Models | Daniel Koch (u. a.) | Taschenbuch | xxii | Englisch | 2025 | Springer | EAN 9783658492175 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a step-by-step introduction to the art of prompt engineering - the most essential skill for the efficient use of generative AI. Since the introduction of ChatGPT at the latest, Large Language Models (LLMs) have become ubiquitous. These systems deliver impressive answers to a wide range of questions, draft concepts and texts, translate, program, and handle tasks. However, the true added value in everyday business only unfolds when the questions are asked correctly. This is because the quality of the answers generated by an LLM depends primarily on the quality of the questions.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions.By leveraging Big Data engineering and popular data cataloguing tools, you'll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. You'll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking.This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business.What You Will LearnExamine thevarious phases of an AI Enterprise Applications implementation.Turn from AI engineer or Data Science to an Intelligent Enterprise Architect.Explore the seamless integration of AI in Big Data Pipelines.Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle.Plan and implement end-to-end large-scale enterprise AI applications with confidence.Who This Book Is ForEnterprise Architects, Technical Architects, Project Managers and Senior Developers. 468 pp. Englisch.

Paperback. Condición: new. Paperback. Artificial Intelligence (AI) is the bedrock of today's applications, propelling the field towards Artificial General Intelligence (AGI). Despite this advancement, integrating such breakthroughs into large-scale production-grade enterprise applications presents significant challenges. This book addresses these hurdles in the domain of large language models within enterprise solutions.By leveraging Big Data engineering and popular data cataloguing tools, youll see how to transform challenges into opportunities, emphasizing data reuse for multiple AI models across diverse domains. Youll gain insights into large language model behavior by using tools such as LangChain and LLamaIndex to segment vast datasets intelligently. Practical considerations take precedence, guiding you on effective AI Governance and data security, especially in data-sensitive industries like banking.This enterprise-focused book takes a pragmatic approach, ensuring large language models align with broader enterprise goals. From data gathering to deployment, it emphasizes the use of low code AI workflow tools for efficiency. Addressing the challenges of handling large volumes of data, the book provides insights into constructing robust Big Data pipelines tailored for Generative AI applications. Scaling Enterprise Solutions with Large Language Models will lead you through the Generative AI application lifecycle and provide the practical knowledge to deploy efficient Generative AI solutions for your business.What You Will LearnExamine the various phases of an AI Enterprise Applications implementation.Turn from AI engineer or Data Science to an Intelligent Enterprise Architect.Explore the seamless integration of AI in Big Data Pipelines.Manage pivotal elements surrounding model development, ensuring a comprehensive understanding of the complete application lifecycle.Plan and implement end-to-end large-scale enterprise AI applications with confidence.Who This Book Is ForEnterprise Architects, Technical Architects, Project Managers and Senior Developers. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.