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Machine unlearning is a branch of machine learning focused on removing specific undesired elements—such as private data, outdated information, copyrighted material, harmful content, dangerous abilities, or misinformation—without needing to rebuild models from the ground up. Machine unlearning is a branch of machine learning focused on removing specific undesired elements—such as private data, outdated information, copyrighted material, harmful content, dangerous abilities, or misinformation—without needing to rebuild models from the ground up.
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Revision as of 09:25, 10 December 2024

Machine unlearning is a branch of machine learning focused on removing specific undesired elements—such as private data, outdated information, copyrighted material, harmful content, dangerous abilities, or misinformation—without needing to rebuild models from the ground up.

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