Experiment with differential privacy using IBM opensourced Differential Privacy Library on GitHub
Diffprivlib is a general-purpose library from IBM for experimenting with, investigating and developing applications in, differential privacy.
Use diffprivlib if you are looking to experiment with differential privacy Explore the impact of differential privacy on machine learning accuracy using classification and clustering models. One can build your own differential privacy applications, using our extensive collection of mechanisms
Diffprivlib supports Python versions 3.6 to 3.8.