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DiffPrivLib is a comprehensive implementation of differential privacy techniques for various data analysis tasks. The library provides a wide range of functionalities, including mechanisms for adding noise to data, privacy-preserving machine learning algorithms, and statistical analysis tools. Diffprivlib is designed to assist developers in incorporating differential privacy into their applications and research projects effectively.

Import the library as follows:

import op_diffprivlib

API Reference

Currently, we support all the methods and classes within the following directories using same function name and signature.