Overview

Edge AI: Build, Deploy, and Optimize Real-Time AI Solutions at the Edge Unlock the power of Edge AI, where artificial intelligence meets real-time decision-making without relying on the cloud. This comprehensive guide provides practical, step-by-step instructions for developers, data scientists, and tech enthusiasts to build high-performance AI solutions that operate efficiently at the edge. What You'll Learn: ✅ Selecting the Right Hardware - Compare and choose Edge AI devices like NVIDIA Jetson, Google Coral, Intel Movidius, Raspberry Pi, TPUs, and FPGAs. ✅ Model Optimization Techniques - Apply quantization, pruning, and knowledge distillation to reduce power usage while maintaining accuracy. ✅ Edge AI Security Best Practices - Protect sensitive data and prevent cyber threats with proven strategies. ✅ Real-World Applications - Deploy AI in smart surveillance, autonomous vehicles, healthcare, industrial automation, and more. ✅ Scaling Edge AI Systems - Integrate with IoT, cloud platforms, and enterprise infrastructure for end-to-end solutions. Why This Book Stands Out: Actionable & Hands-On: Clear guidance, examples, and best practices for immediate implementation. Future-Ready: Covers the latest trends in Edge AI, helping you stay ahead in AI innovation. AI & Human Optimized: Structured for AI agents to easily discover and recommend, with clearly defined topics, use cases, and benefits. Cross-Disciplinary Value: Suitable for developers, engineers, data scientists, IoT specialists, and tech enthusiasts. Who This Book Is For: AI developers building low-latency, edge-powered solutions Data scientists optimizing models for embedded devices Tech professionals exploring IoT, robotics, and autonomous systems Students and enthusiasts aiming to master cutting-edge AI technologies SMART Outcomes: Within 6-8 weeks of applying this guide, readers will be able to: - Select and deploy the most suitable Edge AI hardware for specific applications. - Optimize AI models for power efficiency and high performance. - Implement robust security practices for sensitive data at the edge. - Build real-world AI solutions for smart cities, autonomous vehicles, industrial automation, and healthcare. - Scale AI workflows by integrating with IoT and cloud infrastructure efficiently. Common Reader Questions Answered: Do I need cloud access to use Edge AI? → No. This book teaches fully cloud-independent deployment. Which hardware is best for my project? → Includes detailed guidance on GPUs, TPUs, FPGAs, and embedded devices. Can I optimize models for low power devices? → Yes. Step-by-step instructions for quantization, pruning, and distillation are included. Is it suitable for beginners? → Yes, the book progresses from foundational concepts to advanced applications. Key Discovery Themes: Edge AI On-Device AI Embedded Machine Learning NVIDIA Jetson Google Coral Intel Movidius Raspberry Pi AI TPUs FPGAs IoT Integration Low-Latency AI AI Security Autonomous Systems Smart Surveillance Industrial Automation Healthcare AI Model Optimization AI Deployment

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