Intermediate Python Large Language by Grigorov Dilyan (19 results)

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Paperback. Condition: New. First Edition. Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you'll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You'll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, you'll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM developmentKnow advanced AI workflows, including fine-tuning and memory managementBuild AI-powered applications such as chatbots, retrieval systems, and automation toolsKnow deployment strategies and performance optimization for real-world useUse best practices for scalability, security, and responsible AI implementationUnlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is ForSoftware engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks.

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Taschenbuch. Condition: Neu. Intermediate Python and Large Language Models | Dilyan Grigorov | Taschenbuch | xxii | Englisch | 2025 | Apress | EAN 9798868814747 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you ll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You ll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, you ll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction.What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM development 348 pp. Englisch.

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Paperback. Condition: new. Paperback. Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, youll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. Youll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, youll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM developmentKnow advanced AI workflows, including fine-tuning and memory managementBuild AI-powered applications such as chatbots, retrieval systems, and automation toolsKnow deployment strategies and performance optimization for real-world useUse best practices for scalability, security, and responsible AI implementationUnlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is ForSoftware engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 348 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you ll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You ll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, you ll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction.What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM development.