SensiML’s AutoML process uses the power of cloud computing to aid in the model creation process for ML classifiers intended to run on the most resource-constrained computing platforms at the IoT edge. Ordinarily, creating ML models for this class of devices requires a unique blend of skillsets that include domain knowledge for the application use
Automated machine learning (AutoML), as the name suggests, is the automation of the process for constructing machine learning models. Its use is best illustrated by comparing it to the traditional means for constructing ML models. Without AutoML, the following tasks are left to the modeler to determine based on their understanding of the problem, desired
SensiML offers cutting-edge AutoML software tools enabling developers to quickly create AI-powered sensing applications that run on ultra-low-power microcontrollers that serve as the brains for nearly all IoT devices. Known categorically as TinyML, AI/ML models that can run autonomously on the extreme endpoint nodes (ex. smart doorbells, wearable fitness devices, battery-powered remote sensors) present a
