Embedded Systems Design
Pruning refers to the process of reducing the size of a decision tree or neural network by removing less important nodes or connections. This technique helps streamline models, enhance performance, and reduce computational costs in artificial intelligence and machine learning applications, especially within embedded systems. By eliminating redundancy and focusing on essential components, pruning can improve inference speed and lower memory usage.
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