Xyla Perry (38 results)
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Paperback. Condition: new. Paperback. Master the science - and engineering - behind the world's most powerful AI systems.In Building Large Language Models, you'll learn how today's most advanced AIs - from GPT to LLaMA and Mistral - are trained, optimized, and deployed. This isn't another surface-level overview. It's a hands-on,… code-driven roadmap that takes you from the raw foundations of language modeling to the complete design and scaling of production-grade LLMs.Written by an expert engineer and author in practical AI systems, this guide combines clarity, technical precision, and real-world experience. Each chapter builds on the last - teaching you how to go from understanding transformers to constructing and deploying intelligent models that perform reliably at scale.Whether you're a developer, ML engineer, researcher, or AI enthusiast, this book will show you not just how large language models work, but how to build and optimize them yourself.Inside You'll Learn: Core Foundations: Tokenization, embeddings, attention mechanisms, and transformer architectures explained from the ground up - in plain English.Modern Architectures: Dive deep into encoder-decoder models, decoder-only transformers, state space models, and Mixture-of-Experts systems.Training and Optimization: Learn distributed training (DDP, FSDP, DeepSpeed), mixed precision, checkpointing, gradient accumulation, and FlashAttention.Fine-Tuning Techniques: Apply LoRA, adapters, and prefix/prompt tuning for domain-specific optimization.Evaluation and Scaling: Benchmark with MMLU, HellaSwag, BLEU, and ROUGE; plan data scaling and cost-efficient pipelines.Deployment at Scale: Convert models to ONNX and TensorRT, serve APIs with FastAPI + LangServe, and scale with Docker and Kubernetes.Advanced Topics: Retrieval-Augmented Generation (RAG), vector databases (FAISS, Chroma, Milvus), multimodal LLMs, and agentic AI workflows.Responsible AI: Implement ethical alignment, bias control, data governance, and sustainable model development.Each chapter includes detailed PyTorch examples, Hugging Face integrations, and mini-projects that move from concept to working code.You'll Build Hands-On Projects Including: A next-word prediction model from scratchA 100M-parameter transformer trained with modern optimization techniquesA domain-specific LLM fine-tuned using LoRAA fully functional RAG assistant with embeddings and vector searchA production-ready inference API powered by FastAPI and Docker Every project mirrors real-world workflows used in research labs and enterprise AI engineering teams - ensuring what you learn is directly transferable to your professional or academic work.Who This Book Is ForThis book is for software engineers, AI developers, ML practitioners, data scientists, and researchers who want a complete, practical understanding of LLMs - from architecture to deployment. If you've used ChatGPT or Hugging Face models but want to learn how they're actually built, this book is your gateway.Basic Python and PyTorch knowledge is helpful, but everything is explained step by step, with runnable code and clear guidance for every stage.Why Readers Love This BookDeep yet approachable: Explains complex architectures in plain language without skipping the math or mechanics.Truly hands-on: Every concept comes with code and real datasets - not just theory.Up to date: Covers the latest trends in LLM design - from FlashAttention to MoE and multimodal transformers.Future-ready: Includes advanced insights on agents, long-context memory, sustainability, and LLM governance.Empower yourself to move beyond using AI - to building it. This item is printed on de Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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- Softcover
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Paperback. Condition: new. Paperback. Master the science - and engineering - behind the world's most powerful AI systems.In Building Large Language Models, you'll learn how today's most advanced AIs - from GPT to LLaMA and Mistral - are trained, optimized, and deployed. This isn't another surface-level overview. It's a hands-on,… code-driven roadmap that takes you from the raw foundations of language modeling to the complete design and scaling of production-grade LLMs.Written by an expert engineer and author in practical AI systems, this guide combines clarity, technical precision, and real-world experience. Each chapter builds on the last - teaching you how to go from understanding transformers to constructing and deploying intelligent models that perform reliably at scale.Whether you're a developer, ML engineer, researcher, or AI enthusiast, this book will show you not just how large language models work, but how to build and optimize them yourself.Inside You'll Learn: Core Foundations: Tokenization, embeddings, attention mechanisms, and transformer architectures explained from the ground up - in plain English.Modern Architectures: Dive deep into encoder-decoder models, decoder-only transformers, state space models, and Mixture-of-Experts systems.Training and Optimization: Learn distributed training (DDP, FSDP, DeepSpeed), mixed precision, checkpointing, gradient accumulation, and FlashAttention.Fine-Tuning Techniques: Apply LoRA, adapters, and prefix/prompt tuning for domain-specific optimization.Evaluation and Scaling: Benchmark with MMLU, HellaSwag, BLEU, and ROUGE; plan data scaling and cost-efficient pipelines.Deployment at Scale: Convert models to ONNX and TensorRT, serve APIs with FastAPI + LangServe, and scale with Docker and Kubernetes.Advanced Topics: Retrieval-Augmented Generation (RAG), vector databases (FAISS, Chroma, Milvus), multimodal LLMs, and agentic AI workflows.Responsible AI: Implement ethical alignment, bias control, data governance, and sustainable model development.Each chapter includes detailed PyTorch examples, Hugging Face integrations, and mini-projects that move from concept to working code.You'll Build Hands-On Projects Including: A next-word prediction model from scratchA 100M-parameter transformer trained with modern optimization techniquesA domain-specific LLM fine-tuned using LoRAA fully functional RAG assistant with embeddings and vector searchA production-ready inference API powered by FastAPI and Docker Every project mirrors real-world workflows used in research labs and enterprise AI engineering teams - ensuring what you learn is directly transferable to your professional or academic work.Who This Book Is ForThis book is for software engineers, AI developers, ML practitioners, data scientists, and researchers who want a complete, practical understanding of LLMs - from architecture to deployment. If you've used ChatGPT or Hugging Face models but want to learn how they're actually built, this book is your gateway.Basic Python and PyTorch knowledge is helpful, but everything is explained step by step, with runnable code and clear guidance for every stage.Why Readers Love This BookDeep yet approachable: Explains complex architectures in plain language without skipping the math or mechanics.Truly hands-on: Every concept comes with code and real datasets - not just theory.Up to date: Covers the latest trends in LLM design - from FlashAttention to MoE and multimodal transformers.Future-ready: Includes advanced insights on agents, long-context memory, sustainability, and LLM governance.Empower yourself to move beyond using AI - to building it. This item is Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condition: new. Paperback. Mastering Ghidra for Professionals is your comprehensive guide to mastering one of the world's most powerful open-source reverse engineering platforms. Whether you're a security researcher, malware analyst, penetration tester, or software engineer, this hands-on book equips you with the work…flows, scripts, and real-world case studies you need to analyze complex binaries with confidence.Starting with the fundamentals of Ghidra's architecture and user interface, the book quickly progresses into advanced automation, scripting, and enterprise-scale workflows. You'll learn how to configure Ghidra for large-scale analysis, script repeatable tasks with Python and Java, and deploy headless farms using Docker and CI/CD pipelines. Dynamic analysis, debugging, and advanced decompilation techniques are covered in depth, alongside practical examples drawn from real malware, IoT firmware, and obfuscated code.Through detailed tutorials and practical case studies, you'll uncover how to: Automate symbol recovery, structure reconstruction, and binary diffing.Script powerful custom analyzers using Python, Jython, and Java.Scale Ghidra with Docker, REST, and JSON-RPC integrations.Perform dynamic debugging and trace execution state with precision.Analyze real-world malware, ransomware loaders, shellcode, firmware, and WebAssembly.Collaborate effectively with versioned projects and Git-backed script libraries.Extend Ghidra with plugins and prepare for future releases (including Ghidra 11+).With ASCII flowcharts, command-line walkthroughs, and error-handling strategies, this book focuses on practical, reproducible workflows you can immediately apply in your professional work. Every chapter blends clear explanations with step-by-step execution, making advanced reverse engineering accessible without sacrificing depth.If you want to move beyond theory and learn how to deploy Ghidra in real investigations, enterprise environments, and large-scale reverse engineering projects, this book is for you.Who this book is for: Cybersecurity professionals investigating malware and advanced threats.Reverse engineers analyzing obfuscated binaries, firmware, or proprietary software.Software developers and researchers exploring Ghidra for automation and CI/CD integration.Educators and students looking for a comprehensive, hands-on resource on modern reverse engineering.Take your reverse engineering skills to the next level. With Mastering Ghidra for Professionals, you'll not only learn Ghidra-you'll learn to build scalable, automated, and professional-grade reverse engineering pipelines. 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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- Softcover
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Paperback. Condition: new. Paperback. Book DescriptionReimagine the Command Line. Redefine Developer Productivity.Warp 2.0 is not just another terminal-it's a revolution in how developers think, code, and execute. This definitive guide takes you deep inside Warp's AI-powered ecosystem, where natural language meets precision engi…neering, and the traditional shell evolves into an intelligent agent.From command optimization to agentic workflows, Warp 2.0 teaches you how to transform your terminal into a context-aware, self-correcting environment that understands intent, learns from behavior, and accelerates every part of your development cycle.Written by Xyla Perry a leading author in AI systems and automation, this hands-on guide blends clarity with technical depth-showing you exactly how to harness Warp's AI engine to write, debug, and deploy faster than ever before. Each chapter moves from fundamentals to mastery, helping you build workflows that don't just execute tasks but think with you.Through practical examples, real terminal interactions, and structured best practices, you'll discover how to: Use AI-generated commands that adapt to your system's state and history.Automate repetitive tasks with smart workflows and reusable blocks.Build agentic command chains that operate autonomously and verify results.Integrate with Git, Docker, and CI/CD pipelines for seamless automation.Apply security, privacy, and compliance principles in shared environments.Optimize debugging, performance, and reliability using Warp's inference engine.Each concept is explained in plain English and demonstrated through real command-line examples-no fluff, no filler, just a direct path to mastery.Whether you're a developer, DevOps engineer, or AI enthusiast, Warp 2.0 gives you the tools to reimagine your relationship with the terminal. It's not about typing faster-it's about thinking smarter with every command you run.Perfect ForDevelopers who want to go beyond traditional shells like Bash and Zsh.Engineers automating tasks with AI and agentic logic.Teams building intelligent, reproducible workflows for modern software pipelines.The future of the terminal isn't passive-it's intelligent.With Warp 2.0, you're not just using the command line. You're conversing with it. 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. Condition: new. Paperback. "Mastering the Model Context Protocol: Hands-On AI Agent Design and Context-Aware Workflows"Is your definitive guide to building robust, contextaware AI agents that scale from proof-of-concept to production. Rather than scatter state-management logic across bespoke services, this hands-on ma…nual teaches you how to harness a simple JSON-RPC interface-context.save, context.get, context.prune, and tool.invoke-to centralize conversational memory, orchestrate external tools, and maintain session integrity across distributed clusters.Inside these pages, you'll find real-world scenarios drawn from official reference implementations: from booking flights and triaging support tickets to streaming patient symptoms and firing sub-100 ms trading alerts. Each chapter walks you through theories, clear ASCII diagrams, and fully runnable Python code, then challenges you with mini-projects, troubleshooting deep dives, and end-of-chapter exercises. You'll explore everything from JSON-RPC foundations and sliding-window retention policies to modular plugin architectures, transport layers (WebSockets, gRPC, message queues), observability with structured logging and OpenTelemetry tracing, and scalable deployments on Docker, Kubernetes, serverless platforms, and edge gateways.Whether you're an AI engineer, backend developer, or architect, you'll come away with a battle-tested toolkit for creating next-generation agents that preserve context, handle errors gracefully, and evolve through governed extensions. By the time you finish, you'll not only speak MCP fluently but also be prepared to contribute to open standards, build dynamic agent pipelines, and pioneer tomorrow's adaptive, self-configuring workflows. 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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- Softcover
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- Softcover
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Paperback. Condition: new. Paperback. Build smarter workflows. Connect AI agents. Master automation with n8n and MCP.In today's fast-moving developer landscape, building context-aware automations and AI-driven workflows is no longer optional-it's the new baseline. n8n & MCP: A Developer's Guide for Building Smart Workflows and A…I Agents with Context Protocols is the hands-on manual every modern developer, engineer, and AI practitioner needs to stay ahead.This book bridges n8n, the open-source automation platform, with MCP (Model Context Protocol), the new standard for context-aware AI systems. Together, they unlock the ability to design automations that don't just run tasks, but reason, remember, and adapt. From first setup to enterprise-ready deployments, you'll learn everything you need through practical examples, real-world projects, and developer playbooks.Inside you'll discover how to: Master n8n fundamentals - nodes, triggers, control flow, sub-workflows, and production deployment.Understand MCP deeply - servers, tools, context stores, JSON-RPC calls, and schema design.Connect n8n and MCP securely to orchestrate AI-powered workflows and integrate resource providers like filesystems, APIs, and vector stores.Build real-world projects including an AI chat agent, a retrieval-augmented generation (RAG) pipeline, and multi-agent systems for complex tasks.Apply enterprise practices like observability, incident runbooks, compliance (GDPR/HIPAA), and staged rollouts.Optimize performance and costs with scaling strategies, caching, token budgeting, and CI/CD pipelines.With detailed walkthroughs, JSON examples, TypeScript snippets, and workflow templates, this guide doesn't just explain concepts-it gets you building. Each chapter closes with key takeaways and exercises, ensuring you can apply the material immediately to your own automations.Whether you're: A developer building context-aware automations, An AI engineer designing agents that leverage external tools, orA technical leader bringing enterprise-grade reliability to automation, .this book provides the end-to-end blueprint for success.Future-proof your skills and build workflows that think.n8n & MCP will take you from fundamentals to production-ready systems, giving you the confidence to design, deploy, and scale automation pipelines and AI agents that truly deliver. 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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Seller: California Books, Miami, FL, U.S.A.California Books
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- Softcover
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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condition: new. Paperback. Ollama AI: A Hands-On Guide to Running, Customizing, and Deploying AI Models OfflineBuild Your Own Local AI-No Cloud, No API Keys, No LimitsWhat if you could run powerful AI models like LLaMA, Mistral, Phi, Qwen, Gemma-or even your own custom models-directly on your laptop or PC? No monthly…subscriptions. No internet connection. No data leaving your machine.That's exactly what Ollama makes possible-and this book is your complete roadmap.What This Book CoversThis is not a theoretical AI book. It is a practical engineer's manual for building fully offline AI systems using Ollama.You'll learn step-by-step how to: Install and optimize Ollama on macOS, Windows (WSL2), and Linux.Run open-source AI models locally including LLaMA 2/3, Mistral, Qwen, Phi, CodeLLaMA, and Gemma.Understand GGUF formats, quantization (Q2-Q8), VRAM usage, and GPU vs CPU performance.Customize AI behavior using Modelfiles, system prompts, templates, and LoRA adapters.Build real applications using Python, JavaScript, FastAPI, and REST APIs.Create offline RAG (Retrieval-Augmented Generation) apps using PDFs, FAISS, and Chroma.Deploy local AI services, enable multi-user access, add authentication, rate limiting, and systemd auto-start.Optimize speed and performance-tokens/sec, batching, caching, model versioning, VRAM budgeting.Troubleshoot common issues: CUDA errors, model crashes, API failures, missing GPU drivers.What You'll Build by the EndLocal ChatGPT-style consolePython/JS AI apps connected to Ollama APICustom LLM with a unique personality using ModelfilePDF Document Q&A system (Fully offline RAG)FastAPI-based AI server with streaming responsesA deployable local AI infrastructure you control entirelyWho Is This Book For? Developers & AI Engineers who want full control over LLMs Makers building AI apps without paying for OpenAI/Claude APIs Privacy-focused professionals working offline or in air-gapped systems Students and researchers who want to understand AI at a system level Enterprise teams deploying secure on-prem AI solutionsWhy This Book Is DifferentNo fluff. No generic AI theory.100% hands-on, command-line driven, real projects.Covers future trends like Ollama plugins, MCP agents, local AI marketplaces.Written in simple, developer-friendly language with clear examples.Bring AI back to your machine. Own the model. Own the data. Own the future.Start building today with Ollama AI: A Hands-On Guide to Running, Customizing, and Deploying AI Models Offline. 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. Condition: new. Paperback. Cursor, Windsurf & Lovable for DevelopersBuild Apps Faster with AI Pair Programming, Code Generation, Testing & DeploymentAI is no longer just writing code-it's planning architecture, fixing bugs, generating tests, refactoring legacy systems, and deploying full-stack apps. This book is your…complete guide to mastering the three most powerful AI development tools available today: Cursor, Windsurf, and Lovable.Whether you're a solo developer, startup founder, or part of a software engineering team, this book will show you how to go from idea code test deploy in record time-with AI as your coding partner.What You'll Learn Build real applications using AI pair programming in Cursor Collaborate across entire codebases with multi-file reasoning in Windsurf Generate full MVPs in hours using Lovable (UI, backend, database, auth-everything) Connect OpenAI, Anthropic, and local LLM models to your development workflow Generate clean, modular, production-ready code-not just snippets Write AI-generated unit tests, integration tests and Playwright/Cypress E2E tests Deploy with AI to Vercel, Fly.io, Railway, AWS, Docker & CI/CD pipelines Use AI to debug logs, optimize performance, write PRs, refactor legacy code, and fix failuresInside the Book: 10 Practical Chapters Cursor Mastery - setup, prompting, full-stack app generation, refactoring, test automation Windsurf for Teams - AI-assisted pull requests, code reviews, architecture planning, multi-file refactoring Lovable for Rapid MVPs - build full apps with one prompt: UI + backend + database + auth Code Generation Patterns - Clean Architecture, MVC, services, Prisma, Django, FastAPI, APIs AI for Testing & Debugging - automated unit tests, integration tests, self-healing pipelines CI/CD & Deployment Automation - Dockerfile generation, GitHub Actions, cloud deployment Security, Privacy & Licensing - who owns AI-generated code? MIT vs Apache vs Proprietary Real-World Projects & Case Studies - complete SaaS apps built using AI end-to-end 50+ AI Prompts and a Troubleshooting Guide - instantly reusable for your own projects 24-Hour Final Challenge - build, test, and deploy a new feature using only AI + GitWho This Book Is ForDevelopers who want to code faster and smarter-not harderTeams adopting AI-assisted workflows and automated PRsEngineers tired of boilerplate, setup, and repetitive debuggingFounders building MVPs, SaaS platforms, APIs, dashboards or internal toolsAnyone who wants to future-proof their career as software becomes AI-drivenThe Future of Coding Has Already BegunCursor writes code with you.Windsurf helps your team review, refactor, and scale it.Lovable lets you build full products in a weekend.This is the new development workflow-and this book shows you exactly how to master it.Ready to build faster, ship sooner, and develop with AI as your coding partner?Scroll up and get your copy now. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
