Model navigation refers to the structured movement through machine learning models during training or inference. It is used to optimize performance, reduce computational costs, and streamline decision-making in AI systems. Data scientists and engineers benefit most, as it enhances model selection, debugging, and deployment efficiency in complex workflows.
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