TensorFlow Lite for Microcontrollers
TensorFlow Lite for Microcontrollers is designed to run machine learning models on microcontrollers and other devices with only a few kilobytes of memory. The core runtime just fits in 16 KB on an Arm Cortex M3 and can run many basic models. It doesn't require operating system support, any standard C or C++ libraries, or dynamic memory allocation. Why microcontrollers are important Microcontroller
.NET nanoFramework – Making it easy to write C# code for embedded systems.
.NET nanoFramework makes it easy for C# developers to write embedded applications on microcontrollers units (MCU) with the tools, debugging and features they are used to. This is a free and Open-Source platform for constrained embedded devices. As a developer, you can use your powerful and familiar tools like Microsoft Visual Studio IDE and your .NET C# skills to write code on a microcontroller. P
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GitHub - taiki-e/portable-atomic: Portable atomic types including support for 128-bit atomics, atomic float, etc.
TinyML Benchmark: Fully Connected Neural Networks
Arduino Nano 33 IoT
Nrf52840 Development Board Supports ZigBee/BLE5.0/Thread/SIG Mesh-in Counters from Tools on Aliexpress.com | Alibaba Group
