Efficient ML Computing
Download PDF
Download ePub
Twitter
Facebook
MAIN
2
ML Accelerators
FRONT MATTER
Preface
Dedication
Acknowledgements
Contributors
Copyright
About the Book
MAIN
1
Introduction
2
ML Accelerators
3
Embedded Systems
4
Deep Learning Primer
5
Embedded AI
6
AI Workflow
7
Data Engineering
8
AI Frameworks
9
AI Training
10
Efficient AI
11
Model Optimizations
12
AI Acceleration
13
Benchmarking AI
14
On-Device Learning
15
Embedded AIOps
16
Security & Privacy
17
Responsible AI
18
Sustainable AI
19
AI for Good
20
Robust AI
21
Generative AI
REFERENCES
References
EXERCISES
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
MAIN
2
ML Accelerators
2
ML Accelerators
Coming soon!
Learning Objectives
coming soon.
1
Introduction
3
Embedded Systems