Qeexo AutoML is an end-to-end platform that empowers users to collect, clean, and visualize data to automatically build machine learning models that run at the Edge.
Key Features:
■ Automates the complex and labor-intensive processes of a typical machine learning workflow – no coding or ML expertise required!
■ An end-to-end solution that embeds the data science, machine learning, signal processing, optimization, and embedded engineering needed to deliver AI algorithms for Endpoint/Edge devices – no need to switch between complicated tools
■ Enables a wide range of machine learning methods, including: GBM, XGBoost, Random Forest, Logistic Regression, Decision Tree, CNN, RNN, ANN, Local Outlier Factor, and Isolation Forest
■ Augmented with an easy-to-use interface for labeling, recording, validating, and visualizing time-series sensor data
■ Models generated by Qeexo AutoML perform inference on-device and are optimized for constrained environments: low latency, low power consumption, small footprint
■ Supports Arm® Cortex™- M0 to M4 class MCUs
■ Saves engineering time and cost while eliminating room for error
■ Applications in industrial predictive maintenance, IoT/smart home, wearables, automotive, mobile, and more!
