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"An Abundance of Katherines"

November 31, 2019

Practical privacy in machine learning systems

Catherine Nelson

Data privacy is a huge topic right now for any business using personal data. People are questioning whether they should allow companies to collect data about them, and they are asking about what happens to that data after they hand it over. Machine learning systems often depend on data collected from their users to make accurate predictions. But can we build cool products powered by machine learning while still providing privacy for our users?

Originally presented at ML4ALL 2019

The goal of the ML4ALL Conference is to make applied machine learning accessible to the average software developer or enthusiast. We believe that machine learning should be viewed as a core competency for software developers, and will be a pervasive and essential aspect of almost all human-computer interaction in the near future.

KatieConf 2019. Header image by Nicolas Tissot. Sister conference of JessConf. Contact