awslabs/fast-differential-privacy
Fast, memory-efficient, scalable optimization of deep learning with differential privacy
This helps machine learning engineers and researchers train deep learning models while preserving user data privacy. You input your PyTorch model and training data, and it outputs a differentially private model that protects sensitive information. It's for anyone building or deploying AI models who needs to comply with strict privacy regulations.
139 stars.
Use this if you need to train deep learning models on sensitive data while ensuring strong privacy guarantees without sacrificing training speed or memory efficiency.
Not ideal if your primary concern is not data privacy during model training, or if you are not working with PyTorch deep learning models.
Stars
139
Forks
27
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 22, 2026
Commits (30d)
0
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