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...
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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