emlearn-micropython
Machine Learning and Digital Signal Processing library for MicroPython, enabling TinyML on microcontrollers without C code.
What is emlearn-micropython?
emlearn-micropython is a machine learning and digital signal processing library for MicroPython that enables developers to run efficient ML models on microcontrollers. It provides Python modules for classification, regression, clustering, and signal processing tasks without requiring C programming. The library is designed for TinyML applications on resource-constrained embedded devices.
MicroPython developers working on microcontroller projects who need machine learning capabilities, particularly those building IoT devices, embedded systems, or edge AI applications with limited resources.
Developers choose emlearn-micropython because it provides a scikit-learn-like experience for embedded systems with minimal overhead, offering installable native modules that don't require firmware rebuilds while maintaining high efficiency with inference times under 100 microseconds.
Overview
Machine Learning and Digital Signal Processing for MicroPython
Use Cases
Best For
- Running classification models on ESP32 microcontrollers
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