Four optimization techniques for Machine Learning Inference on Raspberry Pi SBC
Channel: Hardware.ai
Date: 2021-08-25

Link to the article:
https://www.hackster.io/dmitrywat/fast-er-machine-learning-inference-on-raspberry-pi-sbc-5f4d2b

Hardware in the video:
reTerminal
https://www.seeedstudio.com/ReTerminal-with-CM4-p-4904.html

Blink Blink ICE Tower CPU Cooling Fan for Raspberry Pi (Support Pi 4)
https://www.seeedstudio.com/Blink-Blink-ICE-Tower-CPU-Cooling-Fan-for-Raspberry-Pi-Support-Pi-4-p-4215.html

Links to the materials mentioned in the video (tell me if I forgot any):
ARMNN GIthub
https://github.com/ARM-software/armnn

XNNPACK GIthub
https://github.com/google/XNNPACK

TF-MOT Toolkit Documentation
https://www.tensorflow.org/model_optimization/guide

Smart Pruning: Improve Machine Learning Performance on Mobile
https://community.arm.com/developer/ip-products/processors/b/ai-and-ml-blog/posts/smart-pruning

Support FP32 computations using INT8 weights in TensorFlow Lite XNNPACK delegate  
https://github.com/tensorflow/tensorflow/pull/48751

0:10 Why I made this video
1:12 Designing ...
2:17 Reducing ...
3:51 Optimized ...
8:17 ... inference
9:35 Don't set your Pi on Fire

Credits for the music:
Nostalgia Drive - A Nostalgic Synthwave / Chillwave / Retrowave mix
https://www.youtube.com/watch?v=Ek4IRwHBqyo
ED-209 – Frequency 
Photon – Cosmos 

Credits for the artwork:
Awesome Pi On Fire Demo on Bare metal Raspberry Pi 
https://www.youtube.com/watch?v=lGTdHBjlBw8