Pete Warden explains how to use Google’s open source framework to run machine learning models on embedded processors like microcontrollers and DSPs. Discover what you need to get started using the code itself, including hardware, coding tools, and getting the library built and see an example of running speech recognition to spot a “wake word” on a microcontroller with a guide to training, deploying, and running the model.
Pete Warden is the technical lead of the mobile and embedded TensorFlow Group on Google’s Brain team.
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