Lin prescott (43 Ergebnisse)

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

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

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

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

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

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

Soft cover. Zustand: Very Good. Soft cover. MMPB. Light edge wear. Corner bumped. Else, tight and square. Donald Hamilton, Editor. d1821. Original cover price 50 cents. Shelved in plastic. Scarce/rare/hard to find/out of print. WESTERN/SHORTSTORIES.

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

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

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

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

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

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

Taschenbuch. Zustand: Neu. Neuware - Building an application on OpenShift is only the beginning. Production environments demand far more: automated delivery, secure configurations, scalable workloads, observability, reliable infrastructure, and engineering practices that can withstand continuous change.OpenShift Application Engineering takes the next step beyond application development and explores the advanced practices required to engineer and operate production-ready applications on OpenShift.Building on the foundations established in the first book, this volume focuses on the engineering systems surrounding modern applications. You'll explore how to automate application delivery, design repeatable deployment workflows, integrate CI/CD practices, manage application configuration securely, improve scalability, monitor workloads, and troubleshoot complex production scenarios.The book emphasizes practical engineering patterns rather than isolated features. You'll learn not only how to implement these capabilities, but also why they matter and how they fit into a broader cloud-native application lifecycle.Inside the Book, You'll Explore: - Advanced application deployment patterns on OpenShift- Container image management and application build strategies- Kubernetes-native automation and configuration management- CI/CD pipelines and automated application delivery- Git-based development and deployment workflows- Secure management of application configuration and credentials- Application scaling, resource management, and workload optimization- Health checks, observability, logging, and troubleshooting- Reliability and resilience strategies for production workloads- Security considerations for containerized applications- Automation patterns for repeatable application operations- Engineering practices for maintaining applications throughout their lifecycleDesigned for developers, DevOps engineers, platform engineers, SREs, and infrastructure-minded application teams, this book bridges the gap between deploying an application and engineering a production-grade application platform.If Book 1 taught you how to build and deploy applications with OpenShift, this volume shows you how to automate, secure, scale, observe, and engineer those applications for real-world production environments.Build beyond deployment. Engineer for production.…

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware - Learn AI-Powered Coding, Prompting, Debugging, and Development Workflows from the Ground UpGitHub Copilot Essentials is a practical, hands-on guide for developers who want to harness the power of AI to write better code, faster. This book takes you from the fundamentals of generative AI to real-world application of GitHub Copilot in everyday software development.You will learn how to set up and use GitHub Copilot effectively, craft high-quality prompts for better code suggestions, and integrate AI assistance into your coding workflow. The book covers essential topics such as code generation, debugging, test writing, and working across multiple programming languages.Beyond basic usage, this guide helps you understand how to write cleaner, more maintainable code with AI support, improve your problem-solving workflow, and reduce repetitive development tasks. You will also explore responsible AI usage, security considerations, and best practices for integrating Copilot into personal and team projects.By the end of this book, you will be confident using GitHub Copilot as a daily development partner capable of accelerating your learning, improving your productivity, and enhancing the quality of your software projects.…

Taschenbuch. Zustand: Neu. Neuware - Artificial intelligence is transforming the way modern software is built. Large Language Models (LLMs) have made it possible to create intelligent applications that can reason, retrieve knowledge, interact with external tools, automate complex workflows, and collaborate as autonomous agents. But turning these capabilities into reliable, scalable, production-ready systems requires more than prompting a model it requires AI engineering.AI Engineering with LangChain and LangGraph is a comprehensive, hands-on guide that teaches you how to design, build, deploy, and maintain modern AI applications using two of the most powerful frameworks in the LLM ecosystem: LangChain and LangGraph.Whether you're a Python developer, software engineer, machine learning practitioner, or AI enthusiast, this book provides a structured learning path from the fundamentals of LLM application development to advanced agent architectures and enterprise deployment. Through practical examples, real-world projects, and industry best practices, you'll gain the skills needed to build intelligent systems that are robust, scalable, and ready for production.Inside this book, you'll learn how to: - Understand the foundations of AI engineering and modern LLM application architecture.- Build intelligent applications with LangChain's modular components, prompts, models, chains, and runnables.- Create Retrieval-Augmented Generation (RAG) systems that combine LLMs with external knowledge for more accurate and context-aware responses.- Design powerful AI agents capable of reasoning, planning, and using external tools and APIs.- Develop stateful workflows and orchestrate complex agent behavior using LangGraph.- Build collaborative multi-agent systems for research, automation, and decision-making.- Implement memory, conversation management, and long-term knowledge for personalized AI experiences.- Evaluate, monitor, debug, and optimize AI applications using modern observability and testing techniques.- Deploy secure, scalable AI services for real-world production environments.- Apply proven design patterns, architecture principles, and best practices used in professional AI engineering.Throughout the book, you'll work on practical projects that reinforce every concept, helping you move beyond theory and develop the confidence to build sophisticated AI-powered solutions from the ground up.By the end of this book, you'll have the knowledge and practical experience to create enterprise-grade AI applications that leverage LangChain and LangGraph to solve real-world problems equipping you with the skills needed to thrive in the rapidly evolving field of AI engineering.Whether you're building intelligent assistants, knowledge systems, autonomous agents, or next-generation AI products, this book will serve as your complete guide to mastering AI engineering with LangChain and LangGraph.…

Taschenbuch. Zustand: Neu. Neuware - Modern application development increasingly depends on containers, Kubernetes, automation, and cloud-native platforms but understanding how these technologies fit together can be challenging.OpenShift Application Development provides a practical introduction to building and deploying modern applications on OpenShift. Instead of overwhelming you with unnecessary theory, the book focuses on the workflows and concepts developers need to understand to become productive with the platform.Starting with OpenShift and Kubernetes fundamentals, you'll progressively learn how applications are packaged, configured, deployed, exposed, updated, and managed within an OpenShift environment. You'll also explore the relationship between source code, container images, application workloads, services, storage, configuration, and platform resources.Throughout the book, practical examples and hands-on workflows demonstrate how the different pieces fit together, helping you move from a development environment to a functioning application deployment with confidence.Inside the Book, You'll Learn How To: - Understand the architecture and core concepts behind OpenShift- Work with projects, namespaces, workloads, and Kubernetes resources- Build and manage containerized applications- Deploy applications to OpenShift using practical development workflows- Configure applications using environment variables, ConfigMaps, and Secrets- Expose applications through services and routes- Work with persistent application storage- Manage application builds and container images- Update and redeploy applications efficiently- Inspect logs, events, resources, and application status- Diagnose common deployment and runtime problems- Establish development workflows that prepare applications for productionWritten for developers and engineers who prefer practical, implementation-focused learning, this book gives you the foundation required to confidently develop applications on OpenShift.Whether you're new to OpenShift, transitioning from traditional application platforms, or strengthening your Kubernetes skills, OpenShift Application Development provides a clear path from your first deployment to productive cloud-native development.Build it. Deploy it. Understand it. Develop with OpenShift.…

Taschenbuch. Zustand: Neu. Neuware - Building a Knowledge Graph is only the beginning.Modern AI applications increasingly need to retrieve information across connected entities, reason over multiple relationships, coordinate tools and data sources, and operate reliably at production scale. Advanced Knowledge Graphs for LLMs explores the techniques and architectures required to take graph-powered LLM applications beyond basic retrieval and into sophisticated intelligent systems.This volume builds on the foundations of Knowledge Graph construction and LLM integration to explore advanced retrieval, reasoning, agentic workflows, optimization, evaluation, security, and production deployment.You will learn how to: - Design advanced graph-based retrieval architectures- Build Graph RAG systems for complex information needs- Implement multi-hop retrieval and relationship-aware reasoning- Combine graph search, vector search, and semantic retrieval- Improve context selection and reduce irrelevant information- Build LLM-powered agents that interact with Knowledge Graphs- Design agentic workflows for research, question answering, and decision support- Optimize graph queries, retrieval pipelines, and LLM context windows- Evaluate Knowledge Graph quality and LLM application performance- Develop testing, benchmarking, human-in-the-loop, and A/B evaluation strategies- Address security, access control, privacy, and data governance- Design scalable architectures for large Knowledge Graph and LLM workloads- Monitor, maintain, and continuously improve graph-powered AI systems- Transition experimental Knowledge Graph applications into production environmentsThe book focuses on the engineering challenges that emerge when Knowledge Graphs and LLMs move from prototypes to real-world systems.Through practical architectures, implementation patterns, evaluation strategies, and production considerations, you will learn how to build AI applications that can retrieve connected knowledge, reason across relationships, use structured context, and operate reliably at scale.If Foundations of Knowledge Graphs for LLMs teaches you how to build the foundation, this volume teaches you how to extend, optimize, evaluate, and productionize it.Go beyond basic RAG. Build AI systems that can connect knowledge, retrieve context, and reason across relationships.…

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.

Paperback. Zustand: new. Paperback. Artificial intelligence is transforming the way modern software is built. Large Language Models (LLMs) have made it possible to create intelligent applications that can reason, retrieve knowledge, interact with external tools, automate complex workflows, and collaborate as autonomous agents. But turning these capabilities into reliable, scalable, production-ready systems requires more than prompting a model it requires AI engineering.AI Engineering with LangChain and LangGraph is a comprehensive, hands-on guide that teaches you how to design, build, deploy, and maintain modern AI applications using two of the most powerful frameworks in the LLM ecosystem: LangChain and LangGraph.Whether you're a Python developer, software engineer, machine learning practitioner, or AI enthusiast, this book provides a structured learning path from the fundamentals of LLM application development to advanced agent architectures and enterprise deployment. Through practical examples, real-world projects, and industry best practices, you'll gain the skills needed to build intelligent systems that are robust, scalable, and ready for production.Inside this book, you'll learn how to: Understand the foundations of AI engineering and modern LLM application architecture.Build intelligent applications with LangChain's modular components, prompts, models, chains, and runnables.Create Retrieval-Augmented Generation (RAG) systems that combine LLMs with external knowledge for more accurate and context-aware responses.Design powerful AI agents capable of reasoning, planning, and using external tools and APIs.Develop stateful workflows and orchestrate complex agent behavior using LangGraph.Build collaborative multi-agent systems for research, automation, and decision-making.Implement memory, conversation management, and long-term knowledge for personalized AI experiences.Evaluate, monitor, debug, and optimize AI applications using modern observability and testing techniques.Deploy secure, scalable AI services for real-world production environments.Apply proven design patterns, architecture principles, and best practices used in professional AI engineering.Throughout the book, you'll work on practical projects that reinforce every concept, helping you move beyond theory and develop the confidence to build sophisticated AI-powered solutions from the ground up.By the end of this book, you'll have the knowledge and practical experience to create enterprise-grade AI applications that leverage LangChain and LangGraph to solve real-world problems equipping you with the skills needed to thrive in the rapidly evolving field of AI engineering.Whether you're building intelligent assistants, knowledge systems, autonomous agents, or next-generation AI products, this book will serve as your complete guide to mastering AI engineering with LangChain and LangGraph. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Zustand: New. Print on Demand.

Zustand: New. Print on Demand.