Want to use a novel ML architecture, or load your own transfer learning models into Edge Impulse? Create a custom learning block! This feature, which released during Imagine 2022, lets you bring any training pipeline into the Studio — whether written in PyTorch, Keras or scikit-learn — and then treat it like any of our built-in model types. So you can retrain with your own data, and deploy to every MCU or MPU under the sun with full hardware acceleration.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/bring-your-own-model-into-edge-impulse-with-onnx