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邊緣AI實(shí)踐指南（影印版）
邊緣AI實(shí)踐指南（影印版）
Daniel Situnayake, Jenny Plunkett 著
出版時(shí)間：2024年03月
“本書出色地介紹了如何將現(xiàn)代AI技術(shù)與嵌入式系統(tǒng)相結(jié)合?！?br /> ——Elecia White
Making Embedded Systems的作者兼Embedded podcast的主持人
“任何加入這個(gè)激動(dòng)人心的新領(lǐng)域的人都將從這本書提供的深刻見解和清晰思路中受益。”
——Aurélien Geron
YouTube自動(dòng)視頻分類團(tuán)隊(duì)前負(fù)責(zé)人及暢銷書作者
“我能想象得到這本書被用作參考資料，一次又一次地被閱讀?！?br /> ——Fran Baker
Arm公司可持續(xù)發(fā)展與社會(huì)影響總監(jiān)

邊緣AI正在改變計(jì)算機(jī)與真實(shí)世界的交互方式，讓物聯(lián)網(wǎng)設(shè)備可以使用過去由于成本、帶寬或功耗限制而被丟棄的絕大部分傳感器數(shù)據(jù)做出決策。通過嵌入式機(jī)器學(xué)習(xí)等技術(shù)，開發(fā)者可以捕捉人類直覺并將其部署至任何目標(biāo) —— 從超低功耗微控制器到嵌入式Linux設(shè)備。
這本實(shí)用指南為包括產(chǎn)品經(jīng)理和技術(shù)領(lǐng)導(dǎo)者在內(nèi)的工程專業(yè)人士提供了一個(gè)端到端的框架，用于邊緣AI解決現(xiàn)實(shí)世界中的工業(yè)、商業(yè)、科學(xué)問題。你將探索整個(gè)過程的每個(gè)階段，從數(shù)據(jù)收集到模型優(yōu)化，再到調(diào)優(yōu)和測(cè)試，學(xué)習(xí)如何設(shè)計(jì)和支持邊緣AI與嵌入式機(jī)器學(xué)習(xí)產(chǎn)品。邊緣AI注定會(huì)成為系統(tǒng)工程師的標(biāo)準(zhǔn)工具。這份高級(jí)路線圖會(huì)幫助你入門。
● 研習(xí)用于邊緣設(shè)備的AI和機(jī)器學(xué)習(xí)專業(yè)知識(shí)
● 了解哪些項(xiàng)目最適合使用邊緣AI解決
● 探索邊緣AI應(yīng)用的關(guān)鍵設(shè)計(jì)模式
● 學(xué)習(xí)開發(fā)AI系統(tǒng)的迭代工作流
● 建立一支有能力解決現(xiàn)實(shí)問題的團(tuán)隊(duì)
● 遵循負(fù)責(zé)任的AI流程，打造高效產(chǎn)品
● 專用系統(tǒng)：消費(fèi)類、醫(yī)療、工業(yè)、汽車、航空航天
● PCB設(shè)計(jì)，包括可制造性、良率和低噪聲
  1. Foreword
  2. 1. A Brief Introduction to Edge AI
  3. Defining Key Terms
  4. Why Do We Need Edge AI?
  5. Summary
  6. 2. Edge AI in the Real World
  7. Common Use Cases for Edge AI
  8. Types of Applications
  9. Building Applications Responsibly
  10. Summary
  11. 3. The Hardware of Edge AI
  12. Sensors, Signals, and Sources of Data
  13. Processors for Edge AI
  14. Summary
  15. 4. Algorithms for Edge AI
  16. Feature Engineering
  17. Artificial Intelligence Algorithms
  18. Summary
  19. 5. Tools and Expertise
  20. Building a Team for AI at the Edge
  21. Tools of the Trade
  22. Summary
  23. 6. Understanding and Framing Problems
  24. The Edge AI Workflow
  25. Do I Need Edge AI?
  26. Determining Feasibility
  27. Summary
  28. 7. How to Build a Dataset
  29. What Does a Dataset Look Like?
  30. The Ideal Dataset
  31. Datasets and Domain Expertise
  32. Data, Ethics, and Responsible AI
  33. Data-Centric Machine Learning
  34. Estimating Data Requirements
  35. Getting Your Hands on Data
  36. Storing and Retrieving Data
  37. Ensuring Data Quality
  38. Preparing Data
  39. Building a Dataset over Time
  40. Summary
  41. 8. Designing Edge AI Applications
  42. Product and Experience Design
  43. Architectural Design
  44. Accounting for Choices in Design
  45. Summary
  46. 9. Developing Edge AI Applications
  47. An Iterative Workflow for Edge AI Development
  48. Summary
  49. 10. Evaluating, Deploying, and Supporting Edge AI Applications
  50. Evaluating Edge AI Systems
  51. Deploying Edge AI Applications
  52. Supporting Edge AI Applications
  53. What Comes Next
  54. 11. Use Case: Wildlife Monitoring
  55. Problem Exploration
  56. Solution Exploration
  57. Goal Setting
  58. Solution Design
  59. Dataset Gathering
  60. DSP and Machine Learning Workflow
  61. Testing the Model
  62. Deployment
  63. Iterate and Feedback Loops
  64. AI for Good
  65. Related Works
  66. 12. Use Case: Food Quality Assurance
  67. Problem Exploration
  68. Solution Exploration
  69. Goal Setting
  70. Solution Design
  71. Dataset Gathering
  72. DSP and Machine Learning Workflow
  73. Testing the Model
  74. Deployment
  75. Iterate and Feedback Loops
  76. Related Works
  77. 13. Use Case: Consumer Products
  78. Problem Exploration
  79. Goal Setting
  80. Solution Design
  81. Dataset Gathering
  82. DSP and Machine Learning Workflow
  83. Testing the Model
  84. Deployment
  85. Iterate and Feedback Loops
  86. Related Works
  87. Index
書名：邊緣AI實(shí)踐指南（影印版）
國內(nèi)出版社：東南大學(xué)出版社
出版時(shí)間：2024年03月
書號(hào)：978-7-5766-1300-1
原版書書名：AI at the Edge
原版書出版商：O'Reilly Media
Daniel Situnayake
 
Daniel Situnayake在Google領(lǐng)導(dǎo)TensorFlow Lite的開發(fā)宣傳工作，并協(xié)助運(yùn)營TinyML meetup小組。他是Tiny Farms的聯(lián)合創(chuàng)始人，這是美國第一家利用自動(dòng)化技術(shù)以工業(yè)規(guī)模生產(chǎn)昆蟲蛋白的公司。
Daniel Situnayake是Edge Impulse的機(jī)器學(xué)習(xí)負(fù)責(zé)人，負(fù)責(zé)領(lǐng)導(dǎo)嵌入式機(jī)器學(xué)習(xí)的研發(fā)工作。
 
 
Jenny Plunkett
 
Jenny Plunkett是Edge Impulse的高級(jí)開發(fā)者關(guān)系工程師，也是技術(shù)宣講者、開發(fā)者布道師和技術(shù)內(nèi)容創(chuàng)作者。
 
 
The animal on the cover of AI at the Edge is a Siberian ibex (Capra sibirica). They can be found across Asia in places like China, Mongolia, Pakistan, and Kazakhstan. Siberian ibexes are essentially a large species of wild goat. The color of their fur ranges from dark brown to light tan with an occasional reddish tint. Males have large, black, ringed horns while females have smaller gray horns. Both sexes have beards. Their coat lightens in color during the winter and darkens during the summer. They tend to travel in single-sex herds of 5 to 30 animals.

The ideal habitat for Siberian ibexes is above the tree line on steep slopes and rocky scree. They can be found as low as 2,300 feet in semiarid deserts. Their diet consists mainly of grasses and herbs found in scrublands and grasslands.

Because Siberian ibexes are found in abundance in their natural habitat, they are considered a species of Least Concern even though their population is decreasing. Their biggest threat is hunting for food and poaching for sport. Many of the animals on O’Reilly covers are endangered; all of them are important to the world.
購買選項(xiàng)
定價(jià)：154.00元
書號(hào)：978-7-5766-1300-1
出版社：東南大學(xué)出版社