TensorFlow has already made it possible to use trained machine learning models on smartphones. TensorFlow Lite goes one step further and run TensorFlow models on a Raspberry Pi.
uTensor even puts AI on a microcontroller (MCU). They are small and cheap, but they are also energy efficient, slow and have little RAM, which doesn’t make it any easier.
In my presentation I will take a simple machine learning model on TensorFlow and show why it will NOT work with uTensor. But don’t worry, I will also show a working example. I will also go a little bit deeper into TensorFlow operators and you will see also some C/C++ code.
The participant will learn some TensorFlow operators, how to save a model and convert it into C/C++ code, something about uTensor, and why a MNIST example is easier to run on uTensor than a XOR model.
Programming skills and TensorFlow knowledge are an advantage, but not mandatory