Adjusting machine learning models to improve performance or align with specific goals, model manipulation involves techniques like fine-tuning, pruning, or altering parameters. It is used to enhance accuracy, reduce bias, or adapt models to new data. Data scientists and AI developers benefit most, as it optimizes outcomes for applications in healthcare, finance, and autonomous systems.
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