Train machine learning models while keeping user data private with minimal code changes.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeTraining PyTorch models with differential privacy
opacus has 1.9k stars on GitHub. It has been forked 397 times. opacus is written mainly in Python. It has been in active development since 2019. opacus is available under the Apache-2.0 license. Its main topics are deep-learning, differential-privacy, machine-learning, neural-network.
Training PyTorch models with differential privacy
opacus is an open-source project. It is released under the Apache-2.0 license.
Yes. opacus is free and open source — you can use, modify and self-host it.
opacus is available under the Apache-2.0 license.
opacus is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/meta-pytorch-opacus.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.