Model optimization refers to the process of adjusting and refining a model to improve its performance, efficiency, and accuracy in making predictions or classifications. In the context of embedded systems, particularly those utilizing artificial intelligence and machine learning, this concept is crucial for ensuring that models operate effectively within the constraints of hardware resources while maintaining high levels of accuracy and responsiveness.
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