運用 TensorFlow Privacy 在機器學習技術中實現差異化隱私 Reviews

Eduardo M. · Reviewed over 1 year ago

easy

Antonio S. · Reviewed over 1 year ago

Bruna A. · Reviewed over 1 year ago

DJ N. · Reviewed over 1 year ago

Nicholas W. · Reviewed over 1 year ago

Ronaldo M. · Reviewed over 1 year ago

Leung S. · Reviewed over 1 year ago

Fernando M. · Reviewed over 1 year ago

Daniel Sidnei M. · Reviewed over 1 year ago

Piotr B. · Reviewed over 1 year ago

Samruddhi K. · Reviewed over 1 year ago

Sneha M. · Reviewed over 1 year ago

Poojitha Reddy S. · Reviewed over 1 year ago

N Harsha Vardhan R. · Reviewed over 1 year ago

Tarun K. · Reviewed over 1 year ago

Regina B. · Reviewed over 1 year ago

mauro p. · Reviewed over 1 year ago

I don't feel the lab demonstrated the concept of Differential Privacy well enough. Specifically, it seems that the core of the lab is the function "compute_dp_sgd_privacy.compute_dp_sgd_privacy_statement", in that case the lab should have focused on it and on different reports it provides. Trianing the model wasn't really necessary at all in order to call that function.

Yuval W. · Reviewed over 1 year ago

Janani D. · Reviewed over 1 year ago

Joanna S. · Reviewed over 1 year ago

AMIT G. · Reviewed over 1 year ago

Abhishek Kothekar 2. · Reviewed over 1 year ago

Gleison M. · Reviewed over 1 year ago

Riyaz A. · Reviewed over 1 year ago

Hojung J. · Reviewed over 1 year ago