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Introduction
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Classroom Contents
AI-ML Solutions for Low-Power Edge Platforms - Challenges and Opportunities
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- 1 Introduction
- 2 Reminder
- 3 tinyML India Chapter
- 4 Amit Mate Introduction
- 5 GMAC Introduction
- 6 Challenges
- 7 Workflow
- 8 Performance Comparison
- 9 Challenges in AlwaysOn AI
- 10 Example Use Case
- 11 Video Attendance
- 12 Face Recognition Attendance
- 13 How to leverage tinyML
- 14 Questions
- 15 Network acceleration
- 16 Multicore DSPs
- 17 Hardware accelerators
- 18 Cnn
- 19 Story time
- 20 Lowpower devices
- 21 Practical problems
- 22 Unique algorithms
- 23 Nested for loop
- 24 Edge AI trends
- 25 Is there a niche for tinyML
- 26 Future of Edge AI
- 27 Deeplight
- 28 Edge Impulse
- 29 Kixo
- 30 Reality AI
- 31 October 27th
- 32 Closing
