How to Use TinyML for Edge Computing in Embedded Systems

Implementing edge computing in embedded systems is becoming increasingly popular, with several platforms beginning to support it, utilizing TinyML – compact machine learning.

In addition to the eighth edition of Arduino Nano 33 BLE launched by our company, ESP32, QuickLogic’s QuickFeather, and PICO are also building an ecosystem around TinyML.

We will gradually launch activities related to the aforementioned boards.

TinyML is still a new technology, and many users are not familiar with how to get started. To be honest, even Teacher Su doesn’t fully understand it, but knows it is a technology worth exploring.

Learning new knowledge is easier when starting with videos. Today, everyone can first watch two short videos from Digikey, presented by the handsome guy in the pink shirt who talks about KiCad:

I hope this helps everyone understand TinyML better.

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How to Use TinyML for Edge Computing in Embedded Systems

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How to Use TinyML for Edge Computing in Embedded Systems

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