ashor devlin (38 risultati)

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New.

Paperback. Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback. Condizione: new. Paperback. Build real Voice AI products fast with ElevenLabs at the center. This book shows you how to create no-code voice apps and AI phone agents that answer, understand, act, and speak in natural voices. You begin with simple flows and quick wins, then add short API calls and lightweight serverless code where it clearly helps. You will use Model Context Protocol (MCP) to plug in tools and data without tight coupling, and you will apply safe defaults for consent, disclosure, logging, and keys. The goal is simple: ship useful Voice AI features with low latency, predictable cost, and clear guardrails.You will complete three practical builds that cover common needs across support, sales, and learning. The first is an AI phone agent that greets callers, checks consent, captures intent, performs actions, and replies in a steady ElevenLabs voice. The second is a browser voice app with push to talk, live transcription, and spoken responses. The third is an embeddable voice widget for your site that gathers leads or runs surveys. Each build appears first as a no-code version and then as a light API version.The stack stays flexible so you can adopt it in any team. ElevenLabs handles text-to-speech, optional speech-to-text, and voice cloning with consent. MCP exposes tools and knowledge through a clean contract, so you can add calendars, search, records, or custom functions without rewiring your app. n8n, Zapier, or Make orchestrate tasks and state. Small serverless functions sign requests, protect secrets, and implement custom logic. Telephony, hosting, and databases remain swappable, so your choices today will not lock you in tomorrow.Good voice apps rely on design and reliability as much as models. You will learn patterns that keep conversations smooth, including barge-in handling, short reply style, confirmations for risky actions, and clear handoffs to a human. You will add reliability basics such as retries, timeouts, idempotent requests, and caching for common phrases to reduce cost and silence. Safety is built in from the start with consent prompts, disclosure lines where needed, impersonation guardrails, and logs that prove how voices were captured and used.What you'll learn. Plan a voice feature from user intent to spoken reply. Select ElevenLabs settings for stable output and tune latency and cost. Connect transcription, intent parsing, and tool calls into one clear flow you can test step by step. Clone your own voice with consent and use fallback voices when the network stalls. Integrate APIs through MCP to reach calendars, CRMs, search, and private knowledge without exposing secrets in the client. Manage tasks and state with n8n, Zapier, or Make, then add small serverless code for custom rules and transformations.Who this book is for. Creators, marketers, educators, founders, product teams, and developers who want to ship Voice AI features quickly without a machine learning background. If you can follow clear steps and paste short code snippets when needed, you can build an AI phone agent and a browser voice app. The focus is practical skills, clean patterns, and deployable results that fit real budgets and timelines.Why now. Voice AI is moving from novelty to daily interface across customer support, sales, learning, and creator tools. Teams that can builds safe for customers.Start building now. Use the templates, flows, and tested patterns in this book to launch your first voice app this week, add an AI phone agent next, and scale with confidence. Get your copy and turn ElevenLabs, APIs, and MCP into working Voice AI that ships from scratch to production Th Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: New.

Paperback. Condizione: New.

Paperback. Condizione: new. Paperback. This book (AI in Embedded Linux Security) will secure the Future of Embedded Devices-Master Embedded Linux Security from the Inside Out.As embedded Linux systems quietly power the smart devices we rely on-from appliances and wearables to industrial controllers-they've also become prime targets for cyberattacks. In a world of always-connected technology, security can no longer be an afterthought-it must be engineered from the ground up.In this comprehensive and practical guide, a seasoned technology expert with over 30 years of experience arms you with the critical tools and battle-tested strategies to fortify both the hardware and software of your embedded Linux systems. Whether you're building an AI-powered device or securing a legacy appliance, you'll find the knowledge you need to design systems that are resilient, secure, and future-proof.Learn how to think like an attacker-and build like a defender. Explore the inner workings of embedded systems, discover how to harden every layer from boot to BIOS, and master proven techniques for lifecycle protection, secure configuration, and automated updates. This is more than just theory-this is your field guide to security-by-design.What You'll LearnChoose the right hardware platform to balance performance, power, and protectionApply security-by-design principles to every phase of developmentImplement robust features like TPM, LUKS encryption, and secure bootDesign systems that defend against supply chain attacks and misuseBuild and maintain a secure CI/CD pipeline and software supply chainProtect sensitive data and AI models from evolving threatsWho This Book Is ForThis essential guide is written for: Embedded systems engineersLinux security specialistsEmbedded software developersProduct managers and system architectsSuppose you're responsible for designing or securing embedded Linux-based products. In that case, this book will empower you to confidently embed robust security features that withstand real-world attacks and protect users, data, and your reputation.Book Chapters at a GlanceEmbedded Linux and AI Security Challenges in a Connected WorldIntegrating Security and Intelligence from the First Design DecisionsSelecting Secure, High-Performance Hardware for AI-Driven Embedded SystemsChoosing the Right Operating System and AI FrameworksBuilding a Robust, Secure, and AI-Ready Integration ProcessUsing Trusted Platform Modules (TPM) to Protect AI and System IntegrityEncrypting Data to Safeguard AI Models and Sensitive InformationSecuring Boot Processes, Firmware, and BIOS in Embedded Linux AI SystemsStrengthening System Integrity with RPM-OSTree and Immutable Linux ArchitecturesDesigning Resilient Systems to Resist User Misuse and Environmental ThreatsMonitoring Evolving Threats and Updating Embedded AI Security StrategiesSustaining Security and Performance into the FutureConclusion and Future Outlook.BE SMART 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. Condizione: New.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. Are your n8n workflows safe when a dependency shifts at 2 a.m.? Will your logs surface exfiltration before customers notice? This field guide turns fragile automation into hardened, observable, and auditable systems you can trust in production. Automation Security with n8n shows engineers and operators how to design, build, and run n8n with security controls at every stage: source, build, deploy, and run. It uses real tools and concrete configs you can copy, adapt, and ship. Coverage spans containers, embedded Linux bases, and AI connectors that rely on tokens and changing versions. What sets this book apart? It delivers end-to-end patterns that enforce safety by default and prove it with repeatable tests, signatures, and logs that stand up in reviews. Inside, you'll discover: SBOMs with Syft, signed images with Cosign, verified at deploy GitHub Actions that pin versions, run tests, and gate promotions Policy as code with OPA and Conftest for nodes and images Structured logging with field redaction, shipped reliably to ELK or Loki Prometheus alerts and Grafana rules for n8n health and anomalies Kill switches, isolation steps, and token rotation with Vault and scripts Why use this book: Replace ad-hoc fixes with policy-driven, testable controls across the stack Shorten incident timelines with proven playbooks and actionable queries Pass security reviews with traceable signatures, approvals, and audit trails Meet compliance needs while keeping developer speed and CI feedback fast Apply patterns that work with AI connectors, rate limits, and version churn Highlights / mini-TOC: Supply Chain Security for Nodes and Images SBOM Generation with Syft and Policy Review Automated Updates and Approvals via GitHub Actions Logging, Metrics, and SIEM Integration Incident Response and Recovery Compliance and Data Protection CI and Policy-Enforced Pipelines Backups, Restores, and Disaster Recovery Performance, Scale, and Reference Architectures Appendices: Checklists, Labs, and Reference Configs Across the book, you will pin versions, verify sources, and stop surprise changes from entering production. You will scan and sign artifacts, mandate pull-request checks, and promote only builds that meet policy. You will add structured logs with redaction at the source, ship them with agents, and query suspicious patterns in a SIEM. You will set alerts in Prometheus and Grafana, practice kill-switch containment, and rotate compromised keys quickly. You will route data by classification, apply field-level controls for PII, and produce audit trails that match regulatory expectations. You will establish encrypted backups, test restores, and track recovery targets. For teams building connectors on embedded Linux or calling AI services, you will scope tokens, constrain egress, and validate output to prevent quiet failure. Get your copy today and start reading now. This book covers about 95 percent of n8n security solutions - find the chapter that aligns with your issue and solve it right away. 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.

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. 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. Start writing quantum programs today-even if you've never coded. Introduction to Guppylang: Python-Based Quantum Programming for Beginners turns quantum ideas into clear, runnable steps you can try on your laptop-no heavy math, no special hardware. Across 30-40 runnable examples and 3 capstone projects (teleportation, adaptive phase estimation, graph-state patterns), you'll build confidence fast.New language, newly released: Guppylang was publicly announced in August 2025 (with the package posted on PyPI the same week). It's a Python-embedded quantum language designed for modern hybrid workflows-so you write readable Python while expressing true quantum control flow.This book makes quantum programming feel like normal problem solving. You'll use Guppylang to create, transform, and measure qubits in readable Python; apply ownership (linear) types to keep qubits safe; and write measurement-based control with ordinary if/while. A built-in Selene emulator with seeded runs lets you verify results, compare counts, and debug quickly with labeled outputs.Why Guppylang stands outPython-embedded, not a separate silo: write hybrid quantum-classical code with familiar syntax.Ownership / linear qubits: compile-time safety that prevents no-cloning and accidental reuse.Full measurement-dependent control: natural if/while over outcomes-no awkward workarounds.Strong, helpful typing: clear errors and intent-great for teaching and production hygiene.Selene emulator included: deterministic, seeded local runs; parity checks and labeled results for quick validation.Fault-tolerance oriented: supports error-correction workflows and verification-friendly patterns so your code scales toward fault-tolerant devices as they arrive.Robustness in practice: defensive patterns, assertions, and result labeling reduce error indicators and make regressions easy to catch.What You'll LearnZero-to-ready: quick Python primer, clean install, first working programCore quantum, simply: qubits, gates, entanglement, measurementAdaptive logic in Python: branch on measurement outcomesSafety by design: prevent no-cloning and accidental reuseTrust and test: local emulator, reproducible seeds, lightweight checksInterop basics: where import/export fits now-and hardware laterWho It's For: curious beginners and non-coders, students and self-learners, plus developers and educators who want readable, testable quantum code with minimal math.Clear steps. Real programs. Laptop-only. If you can follow Python examples, you can start quantum programming-today.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.