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UID:8a73efd3-b0f8-459f-8474-3f6d285c8af5@support.access-ci.org
DTSTAMP:20241127T110137Z
DTSTART:20241204T170000Z
DTEND:20241204T180000Z
SUMMARY:OpenMined: Introduction to Privacy Preserving Machine Learning
DESCRIPTION:This one-hour live webinar will introduce participants to the f
 undamentals of Privacy Preserving Machine Learning (PPML). The session exp
 lores essential PPML concepts including Federated Learning, Differential P
 rivacy, and Homomorphic Encryption, providing participants with a foundati
 onal understanding of balancing privacy and transparency in ML model devel
 opment. Through practical demonstrations, attendees will learn to integrat
 e privacy-preserving techniques into ML workflows using OpenMined. Partici
 pants will explore PySyft, a powerful open-source framework for secure and
  private machine learning, alongside SyftBox—OpenMined's latest project 
 designed to make development with Privacy-Enhancing Technologies more intu
 itive and developer-friendly.
URL:https://support.access-ci.org/events/7636
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