Differential privacy machine learning frameworks

The following are some of the popular differential privacy machine learning frameworks:

Framework	Implementation
Opacus	PyTorch.
Tensor Flow Privacy	TensorFlow.
Pyvacy	TensorFlow Privacy, but for PyTorch.
JAX(DP)	JAX is Autograd and XLA, brought together for high-performance machine learning research.
Pysyft	Pysyft is a Python library for private, secure machine learning using federated learning and differential privacy. It allows for secure and private training and inference of machine learning models across multiple devices.

Table 5.17 – DP ML frameworks

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