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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unlearning is a branch of machine learning focused on removing specific undesired elements—such as private data, outdated information, copyrighted material, harmful content, dangerous abilities, or misinformation—without needing to rebuild models from the ground up.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unlearning is a branch of machine learning focused on removing specific undesired element, such as private data, outdated information, copyrighted material, harmful content, dangerous abilities, or misinformation—without needing to rebuild models from the ground up.
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{{improve categories|date=December 2024}} {{improve categories|date=December 2024}}

Revision as of 09:25, 10 December 2024

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unlearning is a branch of machine learning focused on removing specific undesired element, such as private data, outdated information, copyrighted material, harmful content, dangerous abilities, or misinformation—without needing to rebuild models from the ground up.

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