Owen Tyrell (18 results)

No Binding. Condition: VG+. 472-14. A VG or better original 8 x 10 still. Size: 8" x 10". Photographic Image.

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.

Condition: New. Print on Demand.

Paperback. Condition: new. Paperback. In today's data-driven world, reliable storage is the foundation of every digital system from small home labs to enterprise-scale infrastructures running critical workloads. TrueNAS, ZFS & Ceph: Unleashing Next-Generation Storage Solutions is a complete, hands-on guide for anyone who wants to build secure, scalable, high-performance storage environments using the most powerful open-source technologies available.Written for homelab builders, system administrators, DevOps engineers, cybersecurity professionals, and enterprise architects, this book takes you beyond theory and into real-world deployment. You'll learn not only how these systems work, but why they matter-and how to design architectures that remain resilient even under failure, load, or disaster.With clear explanations, best-practice workflows, and guided labs, this book helps you build storage infrastructures capable of powering media servers, virtualization clusters, containers, cloud integrations, distributed storage, and mission-critical backup environments.Hands-On Projects & Real DeploymentsThis book includes practical exercises and full architecture guides, such as: - A TrueNAS-powered Plex media server for homelab environments- A ZFS backup vault with automated cloud sync and local snapshots- A high-availability Ceph cluster for Kubernetes or virtualization- Troubleshooting playbooks and professional deployment checklistsEach project is designed to help you build confidence by working through real infrastructure challenges just like you would in production.Why This Book Is DifferentInstead of abstract theory, you'll get actionable workflows, battle-tested configurations, and clear explanations that accelerate mastery. Whether you're deploying your first NAS or designing distributed storage for enterprise workloads, this book provides the practical knowledge and strategic thinking needed to create systems that are fast, reliable, secure, and future-ready.Build the next generation of storage infrastructure and do it with confidence 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.

Paperback. Condition: new. Paperback. Unlock the transformative power of Graph Neural Networks (GNNs) and elevate your AI systems with contextual intelligence and relational reasoning. This comprehensive guide bridges the gap between cutting-edge research and practical application, empowering data scientists, AI engineers, and machine learning practitioners to design, implement, and scale graph-based AI systems for real-world challenges.In today's complex data environments, relationships between entities are just as crucial as the entities themselves. Traditional deep learning approaches often struggle to capture these intricate connections, limiting performance in domains like recommendation systems, fraud detection, knowledge graphs, and social network analysis. This book dives deep into Graph Neural Networks-offering a hands-on roadmap to leverage GCN, GAT, GraphSAGE, and PyTorch Geometric for building high-performance, explainable, and scalable AI systems.What you'll gain from this book: Foundations of Graph Intelligence: Develop a solid understanding of graph theory, graph data structures, and relational representations as the backbone of modern AI systems.Architectures for Real-World Applications: Explore Graph Convolutional Networks (GCN), Graph Attention Networks (GAT), and GraphSAGE, with practical insights on selecting and customizing architectures for specific use cases.Scalable Training Pipelines: Learn to design efficient data pipelines, mini-batch training strategies, and distributed computing approaches for large-scale graphs.Integration with PyTorch Geometric: Master hands-on implementation, from preprocessing graph data to deploying GNN models using the widely adopted PyTorch Geometric framework.Case Studies & Practical Examples: Dive into real-world projects demonstrating social network analytics, knowledge graph completion, recommendation engines, and fraud detection using GNNs.Whether you are building AI systems for enterprise-scale applications or exploring the forefront of research in graph intelligence, this book equips you with the practical skills, architectural know-how, and strategic insights to harness the full potential of Graph Neural Networks. Ground your AI in relational reasoning, deliver explainable insights, and transform complex data into actionable intelligence. 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. Condition: new. Paperback. This book is your complete guide to building next-generation Retrieval-Augmented Generation (RAG) systems powered by knowledge graphs. As LLMs continue to evolve, traditional RAG pipelines struggle with context gaps, shallow retrieval, and limited reasoning. GraphRAG solves these problems by fusing structured knowledge with dynamic retrieval, creating AI systems that are more accurate, explainable, and context-aware.This book gives you a clear, practical, and highly technical foundation for understanding and applying GraphRAG across real-world domains. You'll explore every layer of the modern GraphRAG pipeline-from graph construction and embedding strategies to semantic retrieval, graph reasoning, and generation workflows.Written in a practical, hands-on style, GraphRAG Essentials delivers the tools, patterns, and architectures you need to design, optimize, and deploy knowledge-graph-augmented AI systems at scale.Inside this book, you will learn: - Core GraphRAG principlesHow knowledge graphs enhance retrieval, improve grounding, and deliver richer context to LLMs.- Practical workflows and architecturesStep-by-step pipelines for entity extraction, graph building, retrieval integration, and generation refinement.- Key algorithms and techniquesGraph traversal, semantic similarity search, embeddings, scoring methods, and hybrid retrieval models.- Knowledge graph engineeringSchema design, ontology modeling, graph storage, indexing, and integration with LLM-based systems.- Building GraphRAG applicationsReal-world examples in search, analytics, chat systems, enterprise AI, and domain-specific intelligence.- Performance optimizationHow to improve accuracy, reduce hallucinations, boost retrieval quality, and scale GraphRAG pipelines.- Tooling and frameworksPractical guidance on Neo4j, NetworkX, LangChain, LlamaIndex, and modern graph infrastructure.Who this book is forAI engineers and ML practitionersNLP and knowledge-graph researchersDevelopers building advanced RAG-based applicationsArchitects designing scalable contextual AI systemsAnyone exploring the frontier of AI retrieval and structured reasoningPacked with clear explanations, engineering patterns, and actionable insights, GraphRAG Essentials gives you everything you need to build intelligent, structured, and deeply context-aware retrieval systems.Whether you're enhancing enterprise search, building domain-expert chatbots, or developing custom generative AI applications, this book will help you unlock the full power of GraphRAG. 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. Condition: new. Paperback. Deep learning has entered a new era, one defined by Transformers, diffusion models, graph neural networks, and large-scale architectures that power today's breakthroughs in artificial intelligence. Whether you're a practitioner seeking mastery, a researcher advancing cutting-edge models, or an engineer deploying AI in production environments, this book gives you the deep foundations and practical frameworks needed to build the next generation of intelligent systems.Deep Learning Foundations & Modern Architectures is a complete, end-to-end guide that unifies theory, engineering, and hands-on implementation. Written for the modern AI era, it covers everything from fundamental neural network mathematics to advanced architectures used in generative AI, multimodal systems, and autonomous intelligence.This book is designed to help you understand not only how these systems work, but why they work and how to design, train, optimize, and deploy them with confidence.Inside This Book, You Will Learn How To: Build Strong Deep Learning FoundationsMaster Transformers and Attention-Based ModelsUnderstand and Implement Diffusion ModelsWork with Graph Neural Networks (GNNs)Explore Next-Generation Architectures Train and Optimize Large-Scale Neural NetworksDeploy and Operate Deep Learning Systems in ProductionWho This Book Is ForDeep learning engineersAI researchers & practitionersStudents learning advanced neural networksSoftware engineers transitioning into AIAnyone building or deploying modern AI systemsWhether you're designing a new transformer variant, optimizing model training at scale, or building generative AI applications, this book provides the essential knowledge and architectural patterns you need to succeed in 2025 and beyond.Build the architectures shaping the future of AI.Deep Learning Foundations & Modern Architectures is your blueprint for mastering the models that define tomorrow's intelligent systems. 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. Condition: new. Paperback. AI agents are redefining modern software-powering chatbots, automation systems, productivity tools, and fully autonomous workflows. By combining Python, LLMs, reinforcement learning, and agent frameworks like LangGraph, LangChain, and n8n, developers can now build intelligent systems that reason, plan, and act.This book is a practical guide to creating real agentic AI systems from the ground up.If you want to design conversational agents, build task-oriented automation, or deploy fully autonomous decision-making systems, this book provides the tools and step-by-step skills you need.What You Will LearnCore Agent FoundationsHow agent architectures, memory, planning, and tools workThe difference between reactive, cognitive, and autonomous agentsHow LLMs and machine learning models drive intelligent behavior Practical ML & RL for AgentsKey machine learning and deep learning conceptsReinforcement learning for adaptive decision-makingTraining and improving agent behavior Hands-On ProjectsBuild real systems, including: Conversational chatbots with memoryTask-executing agents using tools and APIsAutomation pipelines with n8nMulti-agent collaboration systemsPython-driven autonomous agents Deployment & ScalingPackaging agents for productionIntegrating APIs, vector databases, and external toolsMonitoring, optimizing, and improving performanceWho This Book Is ForDevelopers, engineers, data scientists, and AI enthusiasts who want to build practical, real-world AI agents. A basic understanding of Python is all you need.Build the Future of Intelligent AutomationStart your journey into agentic AI and learn how to create systems that think, learn, and act.Grab your copy and begin building the next generation of AI agents. 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. Condition: new. Paperback. In today's data-driven world, reliable storage is the foundation of every digital system from small home labs to enterprise-scale infrastructures running critical workloads. TrueNAS, ZFS & Ceph: Unleashing Next-Generation Storage Solutions is a complete, hands-on guide for anyone who wants to build secure, scalable, high-performance storage environments using the most powerful open-source technologies available.Written for homelab builders, system administrators, DevOps engineers, cybersecurity professionals, and enterprise architects, this book takes you beyond theory and into real-world deployment. You'll learn not only how these systems work, but why they matter-and how to design architectures that remain resilient even under failure, load, or disaster.With clear explanations, best-practice workflows, and guided labs, this book helps you build storage infrastructures capable of powering media servers, virtualization clusters, containers, cloud integrations, distributed storage, and mission-critical backup environments.Hands-On Projects & Real DeploymentsThis book includes practical exercises and full architecture guides, such as: - A TrueNAS-powered Plex media server for homelab environments- A ZFS backup vault with automated cloud sync and local snapshots- A high-availability Ceph cluster for Kubernetes or virtualization- Troubleshooting playbooks and professional deployment checklistsEach project is designed to help you build confidence by working through real infrastructure challenges just like you would in production.Why This Book Is DifferentInstead of abstract theory, you'll get actionable workflows, battle-tested configurations, and clear explanations that accelerate mastery. Whether you're deploying your first NAS or designing distributed storage for enterprise workloads, this book provides the practical knowledge and strategic thinking needed to create systems that are fast, reliable, secure, and future-ready.Build the next generation of storage infrastructure and do it with confidence This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.