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TensorFlow Privacy : Learning with differential privacy for training data

When evaluating ML models, it can be difficult to tell the difference between what the models learned to generalize from training and what the models have simply memorized. And that difference can be crucial in some ML tasks, such as when ML models are trained using sensitive data. Recently, new tec...

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Detalles Bibliográficos
Autor principal: Erlingsson, Úlfar (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico Video
Idioma:Inglés
Publicado: O'Reilly Media, Inc., 2020.
Edición:1st edition.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

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