Aimed at devices with low computational power and low memory. The goal is to have the developed models and projects deployed on embedded devices/micro-controllers with low power. Projects cover topics in machine learning, deep learning and computer vision. Models developed will be trained with either ready-avalaible datasets or data collected for specific applicationa. training takes place on high performing computers (e.g. gpu, cloud tpu) and deployed on "tiny" devices for inference only.
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Machine Learning projects for devices with low computing power | low memory such as embedded devices and micro-controllers
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