edge-ml: open source machine learning on microcontrollers #ML #ESP32 #Python

edge-ml is an embedded-first machine learning framework that helps developers build models faster and more robustly with an open-source toolchain for embedded machine learning.

With a few simple steps edge-ml lets you record data, label samples, train models and deploy validated embedded machine learning directly on the edge. edge-ml requires minimal initialization and supports upload in real-time as well as in bulk from the edge.

Pre-recorded data can also be drag-and-dropped as CSV files to the edge-ml cloud storage. Models are generated using AutoML therefore requiring minimal user configuration. The models are optimized for resource-constrained embedded chips based on hardware-aware neural network training.

See more on the edge-ml website and on GitHub.

edge-ml is from the TECO research group, founded in 1993 at the University of Karlsruhe (now KIT – Karlsruhe Institute of Technology) for R&D in applied telematics in close collaboration with industry.


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