关于“使用 TensorFlow Privacy 在机器学习中应用差分隐私”的评价

Jake H. · 已于 about 1 month前审核

us zones are not working jupiter lab is not opening

Sahithi G. · 已于 about 1 month前审核

Ayush V. · 已于 about 1 month前审核

Ushadevi Y. · 已于 about 1 month前审核

Good

Ankur Jain9 .. · 已于 about 1 month前审核

Sujal M. · 已于 about 1 month前审核

Sanika B. · 已于 about 1 month前审核

Karan T. · 已于 about 1 month前审核

Jhon Fernando M. · 已于 about 1 month前审核

이삭 조. · 已于 about 1 month前审核

HaoNT1 N. · 已于 about 1 month前审核

i couldn't get it to run anything. tons of dependency issues and the privacy kernal installing where ever the hell it want. this lab is no where near push and play. it needs lots of troubleshooting.

Jean M. · 已于 about 1 month前审核

Heechang H. · 已于 about 1 month前审核

Jimmy G. · 已于 about 1 month前审核

Poco bien

Dua Z. · 已于 about 1 month前审核

밤 이. · 已于 about 1 month前审核

상태체크 안됨

Heechang H. · 已于 about 1 month前审核

Onkar K. · 已于 about 1 month前审核

Nikita K. · 已于 about 1 month前审核

Saurav G. · 已于 about 1 month前审核

The lab environment experienced several library dependency conflicts and encountered issues locating the installation path for the TensorFlow kernel. Despite successfully completing the tasks, the system fails to flag the lab as 'complete' regardless of multiple attempts. Could you please manually mark this as completed in the system? Kind regards and thank you in advance. Output: DP-SGD performed over 60000 examples with 32 examples per iteration, noise multiplier 0.5 for 1 epochs without microbatching, and no bound on number of examples per user. This privacy guarantee protects the release of all model checkpoints in addition to the final model. Example-level DP with add-or-remove-one adjacency at delta = 1e-05 computed with RDP accounting: Epsilon with each example occurring once per epoch: 10.726 Epsilon assuming Poisson sampling (*): 3.800 No user-level privacy guarantee is possible without a bound on the number of examples per user. (*) Poisson sampling is not usually done in training pipelines, but assuming that the data was randomly shuffled, it is believed the actual epsilon should be closer to this value than the conservative assumption of an arbitrary data order..

Enrique Á. · 已于 about 1 month前审核

Heeralal Kumar S. · 已于 about 1 month前审核

OM M. · 已于 about 1 month前审核

Satyam V. · 已于 about 1 month前审核

the lab is unable to monitor the progress. I'm not able to move forward

shlok p. · 已于 about 1 month前审核