AI at the Edge: Solving Real World Problems with Embedded Machine Learning

Book Description

Edge artificial intelligence is transforming the way computers interact with the real world, allowing internet of things (IoT) devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target–from ultra-low power microcontrollers to flexible embedded Linux devices–for applications that reduce latency, protect privacy, and work without a network connection, greatly expanding the capabilities of the IoT.

This practical guide gives engineering professionals and product managers an end-to-end framework for solving real-world industrial, commercial, and scientific problems with edge AI. You’ll explore every stage of the process, from data collection to model optimization to tuning and testing, as you learn how to design and support edge AI and embedded ML products. Edge AI is destined to become a standard tool for systems engineers. This high-level roadmap will help you get started.

• Develop your expertise in artificial intelligence and machine learning on edge devices
• Understand which projects are best solved with edge AI
• Explore typical design patterns used with edge AI apps
• Use an iterative workflow to develop an edge AI application
• Optimize models for deployment to embedded devices
• Improve model performance based on feedback from real-world use

中文：

书名：AI处于边缘: 用嵌入式机器学习解决现实世界的问题

边缘人工智能正在改变计算机与现实世界的交互方式，允许物联网 (IoT) 设备使用先前由于成本、带宽或功率限制而被丢弃的传感器数据的99% 做出决策。借助嵌入式机器学习等技术，开发人员可以捕获人类的直觉，并将其部署到任何目标 (从超低功耗微控制器到灵活的嵌入式Linux设备)，用于减少延迟，保护隐私并无需网络连接即可工作的应用程序，大大扩展了物联网的功能。

本实用指南为工程专业人员和产品经理提供了一个端到端的框架，用于使用edge AI解决现实世界中的工业，商业和科学问题。在学习如何设计和支持edge AI和嵌入式ML产品时，您将探索过程的每个阶段，从数据收集到模型优化到调优和测试。Edge AI注定要成为系统工程师的标准工具。这个高级路线图将帮助你开始。

• 在边缘设备上开发您的人工智能和机器学习专业知识
• 了解哪些项目最好用edge AI解决
• 探索边缘AI应用程序使用的典型设计模式
• 使用迭代工作流开发边缘AI应用
• 部署到嵌入式设备的优化模型
• 基于实际使用反馈提高模型性能