Colton zhao (63 risultati)

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Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: new. Paperback. Graph RAG Projects: Engineering Advanced Retrieval Systems with Vector Databases and LLMs is a comprehensive, hands-on guide for developers, AI engineers, data scientists, and enterprise teams building next-generation retrieval systems powered by knowledge graphs, vector databases, and large language models (LLMs).In this deep, practical resource, author Zhao Colton introduces a complete blueprint for designing, implementing, and deploying Graph RAG (Graph Retrieval-Augmented Generation) systems capable of semantic understanding, knowledge reasoning, and enterprise-grade retrieval performance. Unlike traditional vector-only RAG setups, Graph RAG brings together graph structures, entity relationships, context linking, semantic indexing, and structured reasoning, creating far more accurate and explainable AI tools.This book is built around real-world projects, code workflows, and production patterns to help you master advanced retrieval architectures, graph construction techniques, graph embeddings, multi-hop reasoning, knowledge extraction, and hybrid search pipelines. Whether you're building semantic search engines, structured reasoning agents, knowledge-aware chatbots, research assistants, or enterprise AI solutions, this guide gives you the tools to engineer sophisticated retrieval workflows at scale.What You Will LearnHow to build Graph RAG pipelines that combine graph databases, embeddings, and language modelsTechniques for knowledge graph modeling, entity extraction, relationship mapping, and ontology designMethods for integrating vector search, graph traversal, topology-based ranking, and hybrid retrievalHow to implement semantic search tools, reasoning engines, and context-aware AI assistantsPractical applications using Neo4j, ArangoDB, NetworkX, and modern vector storesApproaches to structured retrieval, context routing, and LLM reasoning over graph dataWorkflows for building scalable enterprise solutions with graph reasoning, semantic indexing, and multi-step retrieval logicPatterns for real-world deployment, optimization, and evaluation of Graph RAG systemsEvery chapter combines conceptual clarity with implementation depth, ensuring you understand not just what to build, but how to build it effectivelyWho This Book Is ForAI/ML EngineersData ScientistsKnowledge EngineersEnterprise Software TeamsNLP ResearchersDevelopers building retrieval-based AI systemsAnyone interested in knowledge graphs, semantic search, or advanced RAG architecturesWhether you're upgrading an existing RAG pipeline or designing a new retrieval system from scratch, this book will help you create high-performance, knowledge-aware solutions ready for production. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condizione: new. Paperback. Vector Database Systems Engineering is an advanced, practical guide to building intelligent, scalable, and high-performance vector-native architectures for modern AI applications, this book explores the core principles, engineering patterns, and production methodologies behind vector search, embedding management, and semantic retrieval.You'll learn how to evaluate and implement vector databases, optimize similarity search, design hybrid indexing structures, and build large-scale retrieval-augmented generation (RAG) pipelines for real-world applications. From embeddings lifecycle management to distributed storage, from latency optimization to multi-model retrieval routing, this book explains how to construct robust AI data systems that support search, reasoning, and generative intelligence.Packed with detailed architectural breakdowns, hands-on examples, performance benchmarks, and infrastructure blueprints, this guide empowers you to make informed decisions about vector database technologies, system capacity planning, replication strategies, and long-term AI data governance. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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

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

Paperback. Condizione: new. Paperback. LangGraph Engineering with Python is a comprehensive, technical deep dive into modern agentic AI engineering. Written for developers, AI practitioners, and automation architects, this book demystifies LangGraph the groundbreaking framework for building deterministic, controllable, and high-performance AI agent workflows.This book guides you through a complete mastery path: from foundational graph-based reasoning patterns to advanced multi-agent coordination, persistent memory systems, event-driven tasks, and production-grade orchestration. You will learn to construct fully autonomous agents using Python, integrate structured state machines, optimize tool-calling reliability, and design scalable pipelines suitable for enterprise environments.This book goes far beyond "how LangGraph works" and instead teaches how to engineer real AI systems systems with predictable behavior, safe execution boundaries, robust error handling, and modular graph architectures.Whether you're building retrieval-augmented agents, workflow-aware copilots, multimodal systems, or operational AI automation engines, this guide gives you the practical patterns, best practices, and engineering blueprints necessary to deploy at scale.This is the definitive technical handbook for anyone serious about mastering LangGraph in a Python-driven ecosystem. 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. Neo4j Mastery is a comprehensive, future-focused guide for developers, data engineers, analysts, and architects who want to harness the full potential of graph databases to build smarter, faster, and more connected applications.Written by Zhao Colton, this book provides a practical and deeply insightful approach to graph data modeling, Cypher query optimization, knowledge-graph design, graph analytics, real-time recommendations, and enterprise-scale graph solutions.Neo4j continues to lead the industry as organizations demand high-performance data relationships, intelligent search, and AI-ready graph infrastructures. This book equips you with the skills to implement modern graph architectures, integrate Neo4j into complex systems, and leverage its advanced tools to uncover insights impossible to detect with traditional relational databases.Inside, you'll explore: Core Neo4j FundamentalsUnderstand the architecture of Neo4j, how graph databases differ from SQL systems, and why relationships matter in modern applications.Cypher Query Language in DepthMaster pattern matching, filtering, aggregations, traversals, indexing, and performance tuning using Cypher to build powerful, efficient queries.Graph Data ModelingLearn how to design flexible, scalable graph schemas for complex domains such as social networks, fraud detection, logistics, cybersecurity, and recommendation engines.Graph Algorithms and AnalyticsUse advanced Neo4j tools to run PageRank, community detection, similarity scoring, centrality analysis, and pathfinding to uncover hidden patterns and intelligence.Knowledge Graphs & AI IntegrationBuild semantic knowledge structures and integrate graph data with machine learning pipelines, embeddings, and AI-driven reasoning systems.Real-World Graph ProjectsStep-by-step implementations including recommendation systems, fraud analysis, supply chain optimization, customer behavior mapping, and network monitoring.Performance, Scaling & Best PracticesTechniques for clustering, indexing strategies, memory optimization, ETL pipelines, API integration, and securing Neo4j for production environments.Whether you're designing microservices, building AI-enhanced graph applications, optimizing enterprise data workflows, or learning how connected data transforms business intelligence, this book provides everything you need to become an expert Neo4j practitioner.Perfect for beginners looking to start strong and professionals who want to expand into advanced graph engineering.Unlock the power of connected data and transform the way you structure information-with Neo4j, the world's leading graph database platform. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

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

Paperback. Condizione: new. Paperback. This book offers a focused and practical introduction to agentic coding using Claude AI, emphasizing real-world applications rather than abstract concepts. It is designed for developers who want to understand how AI systems can actively participate in the software development process.The book begins by explaining the foundations of agentic systems-how AI models can plan, reason, and execute tasks in structured workflows. It then moves into designing coding agents that assist with writing, reviewing, and refining code in a controlled and reliable way.You will learn how to structure prompts, manage context, and design workflows that allow AI to interact with development environments effectively. The book also explores how to build systems where AI supports debugging, testing, and incremental code improvement.Throughout the chapters, emphasis is placed on responsible and predictable use of AI, ensuring that outputs remain useful, verifiable, and aligned with development goals.By the end of this book, you will have a clear understanding of how to integrate Claude AI into your coding workflow, enabling more efficient development while maintaining control over quality and system design. 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.