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2.privacy-Preserving Machine Learning Through Data Obfuscation by machine.learning.expert2025 is a document available to read on EtoBox.

What is 2.privacy-Preserving Machine Learning Through Data Obfuscation about?

This paper presents a novel methodology for preserving the privacy of training data in machine learning applications through a technique called data obfuscation. By adding random noise to training datasets and augmenting them with synthetic samples, the proposed approach effectively hides sensitive information while maintaining model accuracy. The methodology aims to mitigate privacy threats associated with cloud-based machine learning services, allowing customers to safely share their data without risking

Author

machine.learning.expert2025

Language

EN