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# System prepended metadata

title: Machine Learning on Microcontrollers

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# Machine Learning on Microcontrollers
* [STM32Cube.AI](https://www.st.com/content/st_com/en/stm32-ann.html)
* [Xnor AI](https://www.youtube.com/watch?v=3cD9bpfX9FA&feature=emb_title)
* [nnom](https://github.com/majianjia/nnom) - A higher-level Neural Network library for microcontrollers.
* [nn4mp](https://github.com/correlllab/nn4mp)
* [Embedded Learning Library (ELL)](https://github.com/Microsoft/ELL) - Microsoft's library to deploy intelligent machine-learned models onto resource constrained platforms and small single-board computers.
* [Qualcomm Neural Processing SDK for AI](https://developer.qualcomm.com/software/qualcomm-neural-processing-sdk) - Libraries to developers run NN models on Snapdragon mobile platforms taking advantage of the CPU, GPU and/or DSP.
* [CMSIS NN](https://arm-software.github.io/CMSIS_5/NN/html/index.html) - A collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Cortex-M processor cores.
* [ARM Compute Library](https://developer.arm.com/technologies/compute-library) - Set of optimized functions for image processing, computer vision, and machine learning.
* [uTensor](https://github.com/uTensor/uTensor) - AI inference library based on mbed (an RTOS for ARM chipsets) and TensorFlow.
* [EmbededAI](https://github.com/boralt/EmbeddedAI) - A library that provides elements of AI to C++ applications.
* [kann](https://github.com/attractivechaos/kann) - A lightweight C library for artificial neural networks