Halversen Bjorn (67 results)

Taschenbuch. Condition: Neu. Neuware - Building an LLM prototype is easy. Engineering one that survives production is not. Enterprise Natural Language Processing with LLM is a practical architectural guide for software architects, AI engineers, and developers building production-ready NLP and LLM applications in Python.Move beyond simple prompts and demos to understand the systems, infrastructure, security, and engineering practices required to operate sophisticated generative AI at enterprise scale.Inside, you'll learn how to: - Architect LLM-powered applications, including agentic and conversational systems- Design advanced RAG architectures with hybrid search, re-ranking, query transformation, and graph-based context- Manage prompts, context windows, token limits, versioning, and complex workflows- Build and orchestrate multi-agent systems in Python with routing, human-in-the-loop validation, and execution tracing- Control LLM costs through semantic caching, model routing, batching, and API optimization- Fine-tune and self-host open-source models using LoRA, QLoRA, vLLM, TGI, and TensorRT-LLM- Defend AI applications against prompt injection, jailbreaks, data leakage, and other security risks- Establish LLMOps pipelines for evaluation, A/B testing, model management, and continuous deployment- Design model-agnostic architectures capable of adapting to evolving AI technologiesWhether you're designing an enterprise chatbot, RAG platform, autonomous AI workflow, or broader generative AI infrastructure, this book focuses on the architectural decisions that matter when prototypes become production systems. Build LLM applications that are scalable, secure, observable, and ready for the demands of real-world enterprise AI.…

Taschenbuch. Condition: Neu. Neuware - Discover how to use Windsurf AI to turn ideas into working software faster, even if you are new to AI-assisted development. Windsurf AI for Beginners is a practical, step-by-step guide to vibe coding, AI workflows, prompt-driven development, debugging, project planning, and software creation with artificial intelligence. You will learn how to communicate effectively with Windsurf AI, organize coding tasks, generate and improve code, troubleshoot common problems, and build complete projects with a structured AI workflow. Rather than focusing only on features, this book teaches you how to use Windsurf AI as a practical development partner. From planning your first project to testing and refining a finished application, each chapter helps you build confidence through realistic workflows. Whether you are a beginner, aspiring developer, entrepreneur, student, or creator interested in vibe coding, this guide will help you move from simple prompts to useful software projects while understanding what the AI is doing and when human judgment is still essential.…

Taschenbuch. Condition: Neu. Neuware - Stop babysitting your AI, start shipping code that fixes itself. Tired of AI coding assistants that write a few lines, break the build, and leave you debugging the mess Agentic Workflows with Claude AI shows you how to turn Claude into a true autonomous coding agent-one that plans, writes, tests, diagnoses, and repairs entire systems without constant human hand-holding.This practical guide walks you through the complete autonomous loop: designing multi-file refactoring plans, making Claude write and run its own test suites, teaching it to read stack traces and eliminate root causes, and keeping complex multi-hour tasks on track. You'll learn how to integrate Claude into GitHub Actions for agentic code reviews, migrate deprecated APIs across monorepos at scale, and apply prompt patterns that guide agent behavior instead of just generating syntax.Inside you'll discover: - How to build self-debugging agents that iterate until the code is clean- Techniques for managing state and memory across long-running coding sessions- Strategies for visualizing agent decision paths when tasks go off the rails- Clear rules for when to keep the human in the loop-and when to let the agent run freeWhether you're a senior engineer drowning in technical debt or a team lead looking to multiply development velocity, this book gives you a battle-tested system for orchestrating Claude so it eradicates codebase errors instead of creating them.Start building autonomous coding workflows that actually work.Your next clean commit is waiting.…

Taschenbuch. Condition: Neu. Neuware - Transform your ideas into functional applications using the power of vibe coding and Windsurf AI. Vibe Coding with Windsurf AI shows you how to move from a rough concept to a working app using natural-language prompts, AI-assisted development, iterative building, debugging, and structured project workflows. Instead of spending all your time manually writing code, you will learn how to direct AI effectively while maintaining control over the final product.>Designed for creators, entrepreneurs, aspiring developers, and anyone exploring AI app development, this practical guide provides a clear system for turning ideas into software without relying on random prompting.…

Taschenbuch. Condition: Neu. Neuware - What does it take to move from writing Python scripts to engineering production-ready AI systems Professional Python for AI Engineering is a practical guide for software engineers and data scientists who want to use Python at a professional level for data science, machine learning, and deep learning applications.Rather than focusing on basic Python syntax, this book explores the advanced techniques needed to design, optimize, test, deploy, and maintain robust AI software.You'll explore how to: - Build reproducible Python environments and manage dependencies for AI projects- Optimize memory usage, algorithms, data loading, and expensive computations- Process massive datasets using multiprocessing, Dask, Polars, and out-of-core techniques- Apply architectural patterns to create modular and maintainable machine learning systems- Structure PyTorch and TensorFlow projects for production- Optimize GPU utilization, mixed-precision training, distributed training, and hyperparameters- Build scalable and fault-tolerant model training pipelines- Serialize and deploy models with ONNX, TorchScript, REST APIs, gRPC, and containers- Test, profile, debug, monitor, and continuously improve AI codebases- Connect data pipelines, feature stores, retraining workflows, telemetry, and security into end-to-end AI engineering systemsWhether you are developing machine learning pipelines, deep learning applications, or production AI infrastructure, this book focuses on the engineering practices that help turn experimental code into reliable software.Take your Python skills beyond scripting and into professional AI engineering.…

Taschenbuch. Condition: Neu. Neuware - Successful AI-assisted development depends on more than good prompts. It requires a reliable workflow. Windsurf AI Workflow teaches a structured approach to planning, building, testing, reviewing, and improving software projects with Windsurf AI. You will learn how to break complex development goals into manageable tasks, maintain project context, control AI-generated changes, debug efficiently, and create repeatable systems for future projects. This guide focuses on the complete development lifecycle rather than isolated coding tricks.>Ideal for developers, technical beginners, freelancers, entrepreneurs, and AI coding enthusiasts, this book provides a practical framework for getting more consistent results from Windsurf AI while reducing confusion, unnecessary revisions, and project-breaking changes.…

Taschenbuch. Condition: Neu. Neuware - Your organization is sitting on a massive source of intelligence buried in text. Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information. Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.Inside, you'll learn how to: - Build scalable NLP and text analytics workflows for enterprise data- Apply deep learning architectures, attention mechanisms, and transformers to text- Develop named entity recognition and information extraction systems- Perform sentiment analysis and topic modeling across large text collections- Build semantic search systems using document embeddings and vector databases- Design Retrieval-Augmented Generation (RAG) systems grounded in organizational data- Understand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniques- Adapt NLP and LLM solutions for specialized domains and business workflows- Integrate AI models through enterprise APIs and automated processes- Evaluate accuracy, faithfulness, feedback loops, and business impactFrom unstructured data to actionable intelligence, this book connects advanced AI techniques with the practical realities of enterprise implementation. Build smarter text analytics systems and unlock more value from the information your organization already has.…

Taschenbuch. Condition: Neu. Neuware.

Taschenbuch. Condition: Neu. Neuware - Description The convergence of large language models, retrieval-augmented generation, and knowledge graphs has opened a new frontier in artificial intelligence: the design of autonomous multiagent systems capable of sophisticated reasoning, dynamic collaboration, and reliable execution in complex, real-world environments. AI Agents Handbook delivers a rigorous, end-to-end reference for professionals who must move beyond isolated LLM calls to architect, implement, and operate production-grade agentic platforms. This volume provides the architectural principles, design patterns, and engineering methodologies required to build agents that perceive, plan, act, and coordinate effectively. Readers gain deep expertise in constructing high-fidelity RAG pipelines, integrating structured knowledge graphs for semantic reasoning, implementing advanced agent patterns such as ReAct and Reflexion, and orchestrating multiagent workflows that scale across distributed infrastructure. The handbook systematically addresses the full system lifecycle-from data ingestion and knowledge representation to agent lifecycle management, inter-agent communication protocols, fault tolerance, and continuous evaluation-while maintaining a consistent focus on reliability, observability, and responsible deployment. Special attention is given to the practical challenges that determine success in enterprise and research settings: mitigating hallucinations and retrieval failures, securing agents against prompt injection and adversarial inputs, preserving privacy in multi-party environments, establishing governance and audit mechanisms, and achieving horizontal scalability without sacrificing coherence. Domain-informed case studies and reference architectures illustrate how these components integrate into cohesive solutions for software engineering automation, research acceleration, financial process orchestration, and knowledge-intensive operations. AI Agents Handbook is written for experienced AI engineers, system architects, machine learning researchers, and technical leaders who require both theoretical depth and actionable implementation guidance. Its structured progression from foundational concepts to advanced production considerations equips readers to design agents that are not only intelligent but also robust, maintainable, and aligned with organizational objectives. Master the construction of autonomous multiagent systems that deliver measurable value.Acquire your copy of AI Agents Handbook today and begin building the next generation of scalable, trustworthy, and collaborative AI agent platforms.…

Taschenbuch. Condition: Neu. Neuware - Self-hosted workflow automation platforms give technical teams complete control over data privacy, infrastructure costs, customization, and integration depth. n8n Workflow Automation on Self-Hosted Docker delivers a rigorous, practice-oriented guide to deploying, securing, and extending the n8n platform inside Dockerized environments so you can orchestrate sophisticated workflows, manage them through Git, execute local terminal operations safely, and build native AI agents that run entirely on your infrastructure. The book opens with the architectural foundations of n8n and containerized deployments. You will master host preparation, Docker Compose orchestration, custom image hardening, persistent volume strategies with PostgreSQL, network isolation, and production-grade environment configuration. Subsequent chapters advance through robust workflow design patterns-node semantics, data transformation, conditional logic, error handling, retries, and modular architecture-before focusing on specialized capabilities. A dedicated treatment of n8n's source control and environments feature shows how to connect instances to Git repositories, implement branching and promotion workflows, enable collaborative development, and integrate with CI/CD pipelines for automated testing and deployment of automation assets. Separate coverage addresses the secure activation and disciplined use of command execution nodes inside Docker containers, including permission models, auditing, isolation techniques, and hybrid architectures that combine declarative workflows with imperative local actions.>Security, observability, and operational excellence receive thorough attention: identity and access management, secrets handling, container hardening, structured logging and metrics, performance tuning, scaling with workers and high availability, backup and disaster recovery procedures, and lifecycle management. Real-world architectural patterns illustrate application to DevOps pipelines, internal tooling, data engineering workflows, and autonomous intelligent processes. Intended for experienced developers, DevOps engineers, automation architects, and technical leaders who prioritize sovereignty and extensibility, this resource supplies the precise configurations, architectural patterns, and implementation techniques required to operate a professional-grade, self-hosted n8n platform. Take control of your automation strategy and AI capabilities. Acquire this book today and begin building secure, private, version-controlled, and intelligent workflow systems with n8n on Docker.…

Paperback. Condition: new. Paperback. Building an LLM prototype is easy. Engineering one that survives production is not. Enterprise Natural Language Processing with LLM is a practical architectural guide for software architects, AI engineers, and developers building production-ready NLP and LLM applications in Python.Move beyond simple prompts and demos to understand the systems, infrastructure, security, and engineering practices required to operate sophisticated generative AI at enterprise scale.Inside, you'll learn how to: Architect LLM-powered applications, including agentic and conversational systemsDesign advanced RAG architectures with hybrid search, re-ranking, query transformation, and graph-based contextManage prompts, context windows, token limits, versioning, and complex workflowsBuild and orchestrate multi-agent systems in Python with routing, human-in-the-loop validation, and execution tracingControl LLM costs through semantic caching, model routing, batching, and API optimizationFine-tune and self-host open-source models using LoRA, QLoRA, vLLM, TGI, and TensorRT-LLMDefend AI applications against prompt injection, jailbreaks, data leakage, and other security risksEstablish LLMOps pipelines for evaluation, A/B testing, model management, and continuous deploymentDesign model-agnostic architectures capable of adapting to evolving AI technologiesWhether you're designing an enterprise chatbot, RAG platform, autonomous AI workflow, or broader generative AI infrastructure, this book focuses on the architectural decisions that matter when prototypes become production systems. Build LLM applications that are scalable, secure, observable, and ready for the demands of real-world enterprise AI. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Taschenbuch. Condition: Neu. Neuware - What if your terminal could do more than execute commands What if it could help you build, audit, automate, and ship software Terminal Automation with Claude AI: Mastering the CLI Environment to Accelerate Software Delivery is a practical guide to working with Claude Code and terminal-native AI as an active part of your software development workflow.Move beyond simple autocomplete and browser-based AI tools. Learn how to configure Claude Code, give your projects persistent instructions, work with large codebases, automate repetitive development tasks, and integrate AI into everyday Git and command-line workflows.Inside, you'll discover how to: - Set up Claude Code across macOS, Linux, and Windows- Use terminal-native AI agents for coding, refactoring, and code review- Build persistent project context with CLAUDE.md- Automate shell scripts, regex, and Git hooks- Streamline Git workflows and generate detailed pull request descriptions- Audit codebases and identify potential security vulnerabilities- Sandbox and govern command execution for safer local AI workflows- Extend Claude Code with custom CLI plugins and commandsWhether you're a software developer, DevOps professional, or engineering lead, this book gives you a structured path toward a more AI-powered command-line development environment.If you're ready to move beyond AI autocomplete and explore what autonomous, terminal-native development can do for your workflow, start here.…

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. The MERN stack remains one of the most powerful and productive JavaScript ecosystems for building real-time, feature-rich applications. MERN Stack Utilization by Experienced Engineers delivers the advanced implementation strategies and architectural patterns used by veteran developers to handle complex data persistence and secure authentication in production-grade chat applications. This professional guide explores battle-tested techniques for schema design, real-time data synchronization, scalable messaging architectures, authentication flows, session management, and security hardening specifically tailored to high-concurrency chat systems. Every chapter draws from real-world production experience, addressing challenges such as message history scaling, user presence, end-to-end encryption readiness, and seamless integration across the full MERN pipeline. Written exclusively for experienced fullstack JavaScript engineers, senior MERN developers, technical architects, and engineering leads who already build production applications, this book provides the depth and precision required to elevate chat applications from functional prototypes to robust, scalable, and secure platforms. Ready to master production-grade MERN patterns for data persistence and authentication in modern chat applications? Order your copy today and implement the same battle-tested approaches used by veteran engineers in high-traffic collaborative environments. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. Discover how to use Windsurf AI to turn ideas into working software faster, even if you are new to AI-assisted development. Windsurf AI for Beginners is a practical, step-by-step guide to vibe coding, AI workflows, prompt-driven development, debugging, project planning, and software creation with artificial intelligence. You will learn how to communicate effectively with Windsurf AI, organize coding tasks, generate and improve code, troubleshoot common problems, and build complete projects with a structured AI workflow. Rather than focusing only on features, this book teaches you how to use Windsurf AI as a practical development partner. From planning your first project to testing and refining a finished application, each chapter helps you build confidence through realistic workflows. Whether you are a beginner, aspiring developer, entrepreneur, student, or creator interested in vibe coding, this guide will help you move from simple prompts to useful software projects while understanding what the AI is doing and when human judgment is still essential. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. In the current generation of AI-native application development, the decisive factor separating experimental prototypes from production systems is the quality of integration between large language models and the external systems that supply context and execute outcomes. Ad-hoc tool calling, fragile prompt stuffing, and tightly coupled vendor SDKs create brittle architectures that fracture under load, resist governance, and become impossible to evolve. MCP Integration Scaling delivers the missing engineering discipline: a complete, contract-first methodology for designing, implementing, and operating standardized interfaces that reliably connect language models to custom data providers and action executors at enterprise scale. This book introduces the Model Context Protocol (MCP), a rigorous framework for defining modular, versioned, and observable interfaces that abstract away the complexity of heterogeneous data sources and executable capabilities. Readers will acquire deep expertise in formal contract design, semantic schema alignment, capability declaration, context lifecycle management, secure execution sandboxes, distributed tracing, and resilience patterns specifically engineered for LLM-driven workflows. The text systematically addresses the full spectrum of concerns facing senior practitioners: how to specify retrieval interfaces that deliver precisely scoped, provenance-tracked context without overwhelming model windows; how to model actions with clear transactional boundaries and compensation logic; how to orchestrate multi-step, stateful interactions across providers and executors while preserving isolation and auditability; and how to scale these integrations horizontally while enforcing security, quota, and compliance policies. Through detailed architectural patterns, reference implementations, testing strategies, and production case studies, the book equips AI platform engineers, backend architects, and technical leads with immediately applicable frameworks. You will learn to build SDKs and specification-driven tooling that accelerate development, implement contract and chaos testing regimes that catch integration regressions early, and deploy MCP endpoints using cloud-native and edge patterns that maintain low latency and high availability. Advanced chapters explore federated multi-model topologies, self-describing interfaces, runtime capability negotiation, and optimization techniques that reduce cost and latency while increasing throughput. Whether you are constructing retrieval-augmented generation pipelines, multi-agent orchestration layers, autonomous workflow engines, or enterprise knowledge systems, the methodologies in this volume will allow you to replace fragile point-to-point integrations with durable, evolvable, and governable interfaces. The result is AI applications that remain reliable as data sources, action surfaces, and model capabilities continue to proliferate.Master the design and operation of production-grade MCP integrations. Acquire your copy today and establish the standardized interface layer your AI systems require to deliver consistent, secure, and scalable outcomes. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. What does it take to move from writing Python scripts to engineering production-ready AI systems? Professional Python for AI Engineering is a practical guide for software engineers and data scientists who want to use Python at a professional level for data science, machine learning, and deep learning applications.Rather than focusing on basic Python syntax, this book explores the advanced techniques needed to design, optimize, test, deploy, and maintain robust AI software.You'll explore how to: Build reproducible Python environments and manage dependencies for AI projectsOptimize memory usage, algorithms, data loading, and expensive computationsProcess massive datasets using multiprocessing, Dask, Polars, and out-of-core techniquesApply architectural patterns to create modular and maintainable machine learning systemsStructure PyTorch and TensorFlow projects for productionOptimize GPU utilization, mixed-precision training, distributed training, and hyperparametersBuild scalable and fault-tolerant model training pipelinesSerialize and deploy models with ONNX, TorchScript, REST APIs, gRPC, and containersTest, profile, debug, monitor, and continuously improve AI codebasesConnect data pipelines, feature stores, retraining workflows, telemetry, and security into end-to-end AI engineering systemsWhether you are developing machine learning pipelines, deep learning applications, or production AI infrastructure, this book focuses on the engineering practices that help turn experimental code into reliable software.Take your Python skills beyond scripting and into professional AI engineering. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. Your organization is sitting on a massive source of intelligence buried in text. Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information. Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.Inside, you'll learn how to: Build scalable NLP and text analytics workflows for enterprise dataApply deep learning architectures, attention mechanisms, and transformers to textDevelop named entity recognition and information extraction systemsPerform sentiment analysis and topic modeling across large text collectionsBuild semantic search systems using document embeddings and vector databasesDesign Retrieval-Augmented Generation (RAG) systems grounded in organizational dataUnderstand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniquesAdapt NLP and LLM solutions for specialized domains and business workflowsIntegrate AI models through enterprise APIs and automated processesEvaluate accuracy, faithfulness, feedback loops, and business impactFrom unstructured data to actionable intelligence, this book connects advanced AI techniques with the practical realities of enterprise implementation. Build smarter text analytics systems and unlock more value from the information your organization already has. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.