uingrd/EmbeddedML
《AI嵌入式系统——算法优化与实现》软件工具、例程及教学辅助材料
This project helps embedded systems engineers and developers optimize machine learning algorithms for deployment on resource-constrained hardware. It takes trained machine learning models (like those for image classification or general classification) and converts them into C code, often with optimizations for fixed-point arithmetic, constant multiplication, or ARM NEON instructions. The output is efficient, deployable C code suitable for microcontrollers or other embedded devices.
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Use this if you are an embedded systems engineer or developer who needs to run trained machine learning models on hardware with limited memory and processing power, and you require efficient C code for deployment.
Not ideal if you are solely working with high-level Python environments for model training and inference and do not need to deploy models to embedded C environments.
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Language
Python
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Last pushed
May 07, 2024
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