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Privacy-Preserving Machine Learning with Fully Homomorphic Encryption

Offered By: Google TechTalks via YouTube

Tags

Fully Homomorphic Encryption Courses Machine Learning Courses Cryptography Courses Secure Computation Courses Data Privacy Courses Privacy-Preserving Machine Learning Courses Confidential Computing Courses

Course Description

Overview

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Explore privacy-preserving machine learning techniques using Fully Homomorphic Encryption (FHE) in this 43-minute Google TechTalk presented by Jordan Fréry. Discover how Concrete-ML, an open-source library, enables the seamless conversion of Machine Learning models into FHE counterparts, allowing for zero-trust interactions between clients and service providers. Learn about the potential of deploying ML models on untrusted servers without compromising user data privacy. Gain insights into the latest developments in protecting sensitive information in the digital age from Jordan Fréry, a research scientist at Zama.

Syllabus

Privacy-Preserving Machine Learning with Fully Homomorphic Encryption


Taught by

Google TechTalks

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