calen hawke (29 risultati)

Condizione: New.

Condizione: As New. Unread book in perfect condition.

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

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

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

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

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

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

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

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

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

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

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: new. Paperback. This book is a rigorous, workflow-driven manual for mastering modern prompt engineering. Context Prompt Engineering treats prompts as modular, testable software components and guides readers through the design, orchestration, and evaluation of prompts for large language models (LLMs). It explores context management, reproducibility, and system integration, showing how to build scalable, efficient, and reliable prompt systems for real-world applications. Through detailed examples and practical methods, you will learn how to design reusable prompt templates, chain prompts for complex workflows, manage context effectively, and evaluate outputs using accuracy, safety, and cost metrics. You will also discover how to integrate your prompts with Retrieval-Augmented Generation (RAG), agent systems, and multi-model pipelines for production environments. Whether you are an engineer, researcher, or AI product lead, this book provides the tools and frameworks needed to build persuasive, optimized, and reproducible prompt systems that scale efficiently. Who This Book Is For Prompt engineers and AI developers building robust prompt stacks for production. Researchers focused on prompt evaluation and reproducible experiments. Product teams optimizing token costs, reliability, and output quality. What You Will Learn How to design modular, reusable prompt templates and meta-prompts for diverse tasks. How to implement prompt chaining and orchestration for multi-step workflows. How to manage context using chunking, compression, and token budgeting techniques. How to build evaluation frameworks using accuracy, helpfulness, safety, and cost metrics. How to apply versioning, automated testing, and A/B experimentation to prompts. How to integrate prompts with RAG systems, AI agents, and hybrid pipelines. How to optimize performance for scalability and cost efficiency 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.

Paperback. Condizione: new. Paperback. Unlock the Future of Artificial Intelligence with Hybrid AI Systems: Merging Small and Large Language Models for Efficient IntelligenceThis definitive guide empowers engineers, AI practitioners, and researchers to design and deploy cost-efficient, scalable, and secure AI applications that seamlessly integrate Small Language Models (SLMs) and Large Language Models (LLMs). By combining the agility of lightweight SLMs with the deep reasoning of LLMs, hybrid AI systems deliver context-aware intelligence across edge devices and cloud environments, balancing performance, cost, and sustainability.Dive into a practical roadmap for building hybrid AI ecosystems, packed with actionable insights and hands-on tools. Learn to orchestrate tasks using confidence-based routing, escalation triggers, and telemetry-driven workflows. Master model distillation and compression to optimize SLMs for edge hardware while leveraging LLMs for complex reasoning via secure cloud APIs. From Docker containerization and Kubernetes orchestration to monitoring dashboards with Prometheus and Grafana, this book equips you with production-ready blueprints, Python code samples, and FastAPI integrations. Whether you are deploying real-time assistants on constrained devices or architecting enterprise-scale AI systems, this guide bridges efficiency with innovation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. Build 20 Real-World Workflows with Open-Source Automation is the second book in the Mastering n8n Series by Hawke Calen. This practical guide teaches you how to create powerful automation workflows that improve business efficiency, reduce manual work, and connect different systems using the open-source n8n platform. Designed as a follow-up to Mastering n8n: The No-Code Automation Guide, this book focuses on real-world applications through 20 complete projects. You will learn to automate processes in marketing, sales, customer support, and data management. Each project can be customized to suit your specific needs. The book also covers webhook automation, API integrations, and how to use AI and large language models (LLMs) for smarter, more adaptive workflows. This book is ideal for developers, IT professionals, business owners, operations managers, and no-code or low-code enthusiasts who want to save time, lower costs, and improve productivity through automation. You will learn how to: Build 20 practical n8n workflows for real business cases. Use webhooks and APIs to connect tools and share data easily.Automate key business operations like marketing and sales.Apply AI and LLMs to make workflows more intelligent.Deploy secure, scalable, and reliable automation solutions.With seven easy-to-follow chapters, this book helps you gain the skills to design and maintain professional automation systems. Whether you are new to n8n or looking to advance your skills, this guide will help you create efficient and secure workflows that drive productivity and innovation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condizione: new. Paperback. Claude 4 Engineering in Action is a practical developer's guide to mastering Anthropic's Claude 4 - the revolutionary large language model built on principles of Constitutional AI, long-context reasoning, and secure agentic intelligence. Written by AI systems author Hawke Calen, this book empowers you to design, build, and deploy secure, ethical, and production-grade AI systems powered by Claude 4 and Python. You'll learn to construct autonomous AI agents, orchestrate extended-context pipelines, and build applications that integrate deeply with frameworks such as LangGraph, LangChain, AWS Bedrock, and custom tool-calling architectures. Through a balanced mix of theory, architecture, and hands-on coding examples, you'll explore how to: Implement secure, auditable, and compliant AI agents using Claude 4's constitutional alignment principles. Utilize extended-context reasoning (100K+ tokens) for memory-efficient dialogue and data-rich problem solving. Integrate Claude with Python and enterprise APIs to enable automation, data pipelines, and dynamic task orchestration. Design ReAct-style workflows, multi-agent coordination, and LangGraph pipelines for high-reliability systems.Compare Claude 4 with GPT-4.1, Gemini, and Mistral, identifying performance advantages and domain-specific use cases.Embed ethical AI frameworks, interpretability tools, and trust assurance protocols into your production systems.Future-proof your AI workflows with modular, scalable architectures built on real-world engineering patterns.This is not just a technical guide - it's a comprehensive framework for building responsible, reliable, and high-performance AI systems that meet today's enterprise and ethical standards.Whether you're a machine learning engineer, backend developer, or AI automation architect, this book provides the essential blueprints to bring your Claude 4-powered applications to life - securely, responsibly, and at scale. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. Unlock the power of intelligent AI systems with LangGraph. Dive into the world of advanced AI development with Mastering LangGraph: Building Production-Grade AI Workflows, the definitive guide for creating robust, scalable, and intelligent AI systems using LangGraph, LangChain, and Python-based tools. Written by a seasoned AI engineer with over a decade of experience, this book is designed for technically proficient developers and advanced learners seeking to master the art of building dynamic, multi-agent AI workflows that thrive in real-world applications. This comprehensive guide takes you through the entire process of designing, implementing, and deploying production-grade AI systems. Starting with the fundamentals of dynamic workflows, you will progress to orchestrating autonomous agents and multi-agent systems, mastering advanced techniques for multi-step reasoning, dynamic input handling, and performance optimization. The book concludes with strategies for testing, debugging, and ensuring reliability, preparing your applications for the demands of production environments. The appendix includes an in-depth reference guide with insights into LangGraph architecture, state management, tool integration, and common design patterns. Key Features In-depth theory and practical implementation. Each chapter combines rigorous conceptual explanations with production-ready Python examples, helping you understand both the why and the how of AI workflow design. Real-world examples. Learn through practical applications such as customer support automation, content summarization, and collaborative multi-agent systems. Comprehensive testing and debugging. Discover best practices for unit, integration, and stress testing, along with practical debugging strategies for AI pipelines. Advanced techniques. Explore multi-step reasoning, performance optimization, dynamic adaptability, and distributed execution, with detailed discussions on state management and system reliability. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. This book is a rigorous, workflow-driven manual for mastering modern prompt engineering. Context Prompt Engineering treats prompts as modular, testable software components and guides readers through the design, orchestration, and evaluation of prompts for large language models (LLMs). It explores context management, reproducibility, and system integration, showing how to build scalable, efficient, and reliable prompt systems for real-world applications. Through detailed examples and practical methods, you will learn how to design reusable prompt templates, chain prompts for complex workflows, manage context effectively, and evaluate outputs using accuracy, safety, and cost metrics. You will also discover how to integrate your prompts with Retrieval-Augmented Generation (RAG), agent systems, and multi-model pipelines for production environments. Whether you are an engineer, researcher, or AI product lead, this book provides the tools and frameworks needed to build persuasive, optimized, and reproducible prompt systems that scale efficiently. Who This Book Is For Prompt engineers and AI developers building robust prompt stacks for production. Researchers focused on prompt evaluation and reproducible experiments. Product teams optimizing token costs, reliability, and output quality. What You Will Learn How to design modular, reusable prompt templates and meta-prompts for diverse tasks. How to implement prompt chaining and orchestration for multi-step workflows. How to manage context using chunking, compression, and token budgeting techniques. How to build evaluation frameworks using accuracy, helpfulness, safety, and cost metrics. How to apply versioning, automated testing, and A/B experimentation to prompts. How to integrate prompts with RAG systems, AI agents, and hybrid pipelines. How to optimize performance for scalability and cost efficiency 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.

Paperback. Condizione: new. Paperback. Unlock the Future of Artificial Intelligence with Hybrid AI Systems: Merging Small and Large Language Models for Efficient IntelligenceThis definitive guide empowers engineers, AI practitioners, and researchers to design and deploy cost-efficient, scalable, and secure AI applications that seamlessly integrate Small Language Models (SLMs) and Large Language Models (LLMs). By combining the agility of lightweight SLMs with the deep reasoning of LLMs, hybrid AI systems deliver context-aware intelligence across edge devices and cloud environments, balancing performance, cost, and sustainability.Dive into a practical roadmap for building hybrid AI ecosystems, packed with actionable insights and hands-on tools. Learn to orchestrate tasks using confidence-based routing, escalation triggers, and telemetry-driven workflows. Master model distillation and compression to optimize SLMs for edge hardware while leveraging LLMs for complex reasoning via secure cloud APIs. From Docker containerization and Kubernetes orchestration to monitoring dashboards with Prometheus and Grafana, this book equips you with production-ready blueprints, Python code samples, and FastAPI integrations. Whether you are deploying real-time assistants on constrained devices or architecting enterprise-scale AI systems, this guide bridges efficiency with innovation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: new. Paperback. Build 20 Real-World Workflows with Open-Source Automation is the second book in the Mastering n8n Series by Hawke Calen. This practical guide teaches you how to create powerful automation workflows that improve business efficiency, reduce manual work, and connect different systems using the open-source n8n platform. Designed as a follow-up to Mastering n8n: The No-Code Automation Guide, this book focuses on real-world applications through 20 complete projects. You will learn to automate processes in marketing, sales, customer support, and data management. Each project can be customized to suit your specific needs. The book also covers webhook automation, API integrations, and how to use AI and large language models (LLMs) for smarter, more adaptive workflows. This book is ideal for developers, IT professionals, business owners, operations managers, and no-code or low-code enthusiasts who want to save time, lower costs, and improve productivity through automation. You will learn how to: Build 20 practical n8n workflows for real business cases. Use webhooks and APIs to connect tools and share data easily.Automate key business operations like marketing and sales.Apply AI and LLMs to make workflows more intelligent.Deploy secure, scalable, and reliable automation solutions.With seven easy-to-follow chapters, this book helps you gain the skills to design and maintain professional automation systems. Whether you are new to n8n or looking to advance your skills, this guide will help you create efficient and secure workflows that drive productivity and innovation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: new. Paperback. Claude 4 Engineering in Action is a practical developer's guide to mastering Anthropic's Claude 4 - the revolutionary large language model built on principles of Constitutional AI, long-context reasoning, and secure agentic intelligence. Written by AI systems author Hawke Calen, this book empowers you to design, build, and deploy secure, ethical, and production-grade AI systems powered by Claude 4 and Python. You'll learn to construct autonomous AI agents, orchestrate extended-context pipelines, and build applications that integrate deeply with frameworks such as LangGraph, LangChain, AWS Bedrock, and custom tool-calling architectures. Through a balanced mix of theory, architecture, and hands-on coding examples, you'll explore how to: Implement secure, auditable, and compliant AI agents using Claude 4's constitutional alignment principles. Utilize extended-context reasoning (100K+ tokens) for memory-efficient dialogue and data-rich problem solving. Integrate Claude with Python and enterprise APIs to enable automation, data pipelines, and dynamic task orchestration. Design ReAct-style workflows, multi-agent coordination, and LangGraph pipelines for high-reliability systems.Compare Claude 4 with GPT-4.1, Gemini, and Mistral, identifying performance advantages and domain-specific use cases.Embed ethical AI frameworks, interpretability tools, and trust assurance protocols into your production systems.Future-proof your AI workflows with modular, scalable architectures built on real-world engineering patterns.This is not just a technical guide - it's a comprehensive framework for building responsible, reliable, and high-performance AI systems that meet today's enterprise and ethical standards.Whether you're a machine learning engineer, backend developer, or AI automation architect, this book provides the essential blueprints to bring your Claude 4-powered applications to life - securely, responsibly, and at scale. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: new. Paperback. Unlock the power of intelligent AI systems with LangGraph. Dive into the world of advanced AI development with Mastering LangGraph: Building Production-Grade AI Workflows, the definitive guide for creating robust, scalable, and intelligent AI systems using LangGraph, LangChain, and Python-based tools. Written by a seasoned AI engineer with over a decade of experience, this book is designed for technically proficient developers and advanced learners seeking to master the art of building dynamic, multi-agent AI workflows that thrive in real-world applications. This comprehensive guide takes you through the entire process of designing, implementing, and deploying production-grade AI systems. Starting with the fundamentals of dynamic workflows, you will progress to orchestrating autonomous agents and multi-agent systems, mastering advanced techniques for multi-step reasoning, dynamic input handling, and performance optimization. The book concludes with strategies for testing, debugging, and ensuring reliability, preparing your applications for the demands of production environments. The appendix includes an in-depth reference guide with insights into LangGraph architecture, state management, tool integration, and common design patterns. Key Features In-depth theory and practical implementation. Each chapter combines rigorous conceptual explanations with production-ready Python examples, helping you understand both the why and the how of AI workflow design. Real-world examples. Learn through practical applications such as customer support automation, content summarization, and collaborative multi-agent systems. Comprehensive testing and debugging. Discover best practices for unit, integration, and stress testing, along with practical debugging strategies for AI pipelines. Advanced techniques. Explore multi-step reasoning, performance optimization, dynamic adaptability, and distributed execution, with detailed discussions on state management and system reliability. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.