In machine learning, model efficiency measures how well a system balances accuracy with computational cost. It's used to optimize neural networks for faster inference, lower energy use, and reduced memory footprint. Developers benefit from quicker deployment on edge devices, while end users enjoy responsive apps and sustainable AI.
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