Using Edge Impulse, it is possible to create intelligent device solutions embedding tiny Machine Learning and DNN models. The Cloud-based solution abstracts the complexity of real-world sensor data collection and storage, data features extraction, ML and DNN models training and conversion to embedded code, and model deployment on STM32 MCU devices. Without local AI framework installation, engineers can generate and export the model into their STM32 projects with a single function call. All generated Neural Networks now fully utilize STM32Cube.AI to ensure that they run as fast and energy efficiently as possible, and firmware can be fully customized using STM32CubeMX.
This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/machine-learning-for-all-stm32-developers-with-stm32cube-ai-and-edge-impulse/