Machine Learning Systems
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Appendices
F
Case Studies
FRONT MATTER
Preface
Dedication
Acknowledgements
Contributors
Copyright
About the Book
MAIN
1
Introduction
2
Embedded Systems
3
Deep Learning Primer
4
Embedded AI
5
AI Workflow
6
Data Engineering
7
AI Frameworks
8
AI Training
9
Efficient AI
10
Model Optimizations
11
AI Acceleration
12
Benchmarking AI
13
On-Device Learning
14
Embedded AIOps
15
Security & Privacy
16
Responsible AI
17
Sustainable AI
18
AI for Good
19
Robust AI
20
Generative AI
REFERENCES
References
LABS
Setup Nicla Vision
CV on Nicla Vision
Object Detection
Audio Feature Engineering
Keyword Spotting (KWS)
DSP - Spectral Features
Motion Classification and Anomaly Detection
Appendices
A
Tools
B
Datasets
C
Model Zoo
D
Resources
E
Communities
F
Case Studies
Appendices
F
Case Studies
Appendix F: Case Studies
Learning Objectives
Coming soon.
E
Communities